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Should I go back for 2nd PhD in applied field this time?
I finished my PhD in 2017 in a psychology field that is mostly academic (non-clinical), so it is basically impossible to find jobs outside of academia that don't require a huge move.
I have a current visiting position that will expire potentially next year (though previous VAPs at the school have been extended). My research productivity has declined while teaching- and I really enjoy teaching and have gotten good reviews, but there do not seem to be many positions that hire only on that basis. Additionally, I've grown a bit tired of the prescribed way research is incentivized and framed in my field.
To add to that, my girlfriend is attached to the current area with permanent work and family/friends are all connected to where we currently live. Jobs in this area pertaining to my work seem nearly impossible, but the location is ideal.
However, there are a lot of applied types of jobs in the area in psychology. Should I consider going back for a PhD in for example, counseling psychology so as to increase my work potential? To me it sounds crazy but the very real possibility of having no work or having to take crummy adjunct positions for the rest of my life is enough to make me consider it. I've considered applied masters degrees as well which would be enough to get a job, but not great ones for the cost (although maybe best for my circumstance?). I also should mention that I really find the applied aspect of this work appealing, and would love to be more involved with people through it so it's not as though my heart wouldn't be in it.
The job market is truly terrible as far as I can tell, and I feel that I'd have a much better chance if I got out of my current field which feels completely pigeonholed. However, spending another 5 years (assuming I get in) in school being broke again plus whatever supervised work comes after makes me tired just thinking of it.
The bottom line is, I want job security. Outside of tenure lines, which feel like a far flung possibility at this point, I don't know how to feel secure with my current degree. I know the real kicker is probably my location restriction, but I just don't think it would be worth it to give up my relationships at this point in my life when things finally seem to work out. If anyone knows of/has had any similar experience, I would greatly appreciate any advice.

What field of psychology did you complete, might I ask? I find it surprising that it's difficult to find work if you had good training in quantitative methods--there are plenty of jobs for psychology Ph.D. grads in the industry for data analytics, operations, consumer behavior, etc.

Aren't there other ways of transitioning between related fields than another PhD?

My field is social psychology. If there are other ways of transitioning into an applied field, I haven't been able to find any real information on it. Experimental psychology is typically seen as "non-qualifying experience" for these applied jobs.

Why would you get a PhD in counseling psychology instead of a master's in counseling psychology (or a similar field) if your objective is to have credentials for a job? Don't such master's programs usually have some sort of paid work in the discipline as part of the program?

I'm wondering, but can you do the clinical hours required to get licensure? I'm also in Psychology but I've seen people work in areas like Development Psychology switch to clinical practice and become a licensed therapists after their "unrelated" doctorate by completing the 3,000 (or so) hours of supervised clinical practice. This varies from state to state and country to country, but here's information about the US for reference: https://www.psychologist-license.com/articles/psychologist-licensure.html

Otherwise, there are also some relatively cheap online Master's Degrees from reputable universities that may offer data analytical training if you're interested in going that route for job prospectives. For instance, the Master's of Science in Analytics from Georgia Tech is only $9,900 in tuition: https://www.edx.org/masters/online-master-science-analytics-georgia-tech

Duplicate https://academia.stackexchange.com/questions/17232/is-doing-two-phds-a-good-path Also, there is a lot of rant and not much question here.

Instead of looking to start a second PhD, is there any way you could find a post-doc in a more applied field? This would be a much shorter route to obtaining more clinical/applied experience. I do not know how licensure works in your specific locale (i.e. do you need to have a certain specialization in a psychology PhD to be licensed?), but if all you need is experience then a post-doc may be the better option. Post-docs usually are much shorter than a full PhD and also pay much better (relatively speaking).

Jobs in this area pertaining to my work seem nearly impossible, but the location is ideal.

One of the worst things you can do early career is place artificial restraints on your job search. Yes, your girlfriend has connections to the current location. Does she want to live there the rest of her life, even if it means you are unemployed? I have had several early career people that I've mentored tell me that they cannot find any jobs, only to discover that they are exclusively looking in their hometown in Alabama with 1500 residents (or whatever). They tell me "Oh, but that's where my family lives!" That's great, if your family is willing to support you financially.
Any location where you are unemployed long term without any prospects is not "ideal."  Not to be harsh, but you may need to decide whether you would rather have your current girlfriend or a job. This is entirely not my business, but perhaps a girlfriend who refuses to move so that you can find a better opportunity is not a girlfriend you want long term. This is especially true if she is planning on looking to you for any form of financial support. I understand that there is a balance there; your career certainly does not take inherent precedence over hers. But depending on what your long terms plans are together, she and you may need to have a discussion about moving or breaking up.

As has been mentioned in the comments, it is also possible that you could find work in fields that are not directly related to clinical psychology. I work with some researchers in the engineering industry who do "human factor analysis." They help companies (mostly the defense industry) determine how to make their products safer from a human-error standpoint. Many of these researchers have PhDs in psychology. Developing the quantitative skills to do work like this would be much easier than getting a second PhD. Similar work can be found in fields like political science and legal science (i.e. as a trial scientist). These are often directly related to social psychology.

The bottom line is, I want job security.

I think your real question is, "How do I get job security?"  I think the answer is that is not a realistic goal.
Job security occurs only when revenue grows faster than expenses in the long term.  This is necessary but not sufficient.  Currently, in academia, expenses usually grow faster than revenue.  This will often lead to layoffs or institutional closure.  Tenure (or unions, or laws, or anything) provides no protection against the closure of the institution when it is unable to pay workers.  Outside academia, very few industries can provide job security over a period of decades.


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In performing a comparison, how can I get authors to actually respond to a request for source code?
I'm doing my PhD in computer science and am working in computer vision. I have come up with an algorithm that my supervisors consider to be promising and publishable. It took me a long time to get these results.
Now the thing is that I have to compare my code to other recent papers tackling the same issue. Which I understand is very necessary as to show how my work compares to previous work. My supervisors want me to compare against at least 4 or 5 other recent papers.
The problem is that the database I am using is very recent and no journal papers have till yet used it. So the other solution left for me is to read the journal papers, understand it and try to implement their code.
This will definitely take way too long and in my opinion waste a lot of time. These journal papers are very advanced (obviously) and implementing their results on my own will take up a lot of my time whose only sole purpose is to get a result.
One solution would be to email the authors and ask politely for their source code, but I found out that many authors don't reply.
This question Can I request the code behind a research paper from the author? stated that they were more likely to get a response if they promised to add that author as a co-author in their paper. I do not want to do that as that would be being dishonest as I see no sense in adding the author to my paper just because I compared my work against his, and if I am to compare against 5 papers then that will be a very long list of authors.
Maybe I am asking for something that is frowned upon. Or maybe not asking in the right manner?
I emailed the authors and asked for their code solely to test their work on my database for comparison purposes, which gets no replies. Am I doing something wrong?

"These journal papers are very advanced (obviously) and implementing their results on my own will take up a lot of my time whose only sole purpose is to get a result." - And you're saying that while you may be getting a publication out of it. While I do see ethical concerns with refusing to share any source code required to reproduce experiments, and not replying at all certainly goes into rude territory, assuming that you asked with a reasonable level of politeness, from the point of view of those other authors, checking whether they can give you such source code will take up ...

... quite some of their time, which will not necessarily directly contribute to their research. (tl;dr: They should answer, but I can see why they might not want to.)

I assume that each of those 5 papers reported the database they tested with, and the results they obtained. Can you get those databases? If so, perhaps you could run your code against each database, and compare your results to the results they reported. It might be easier than trying to replicate their code or even get their code running. The ideal situation would be if all 5 papers used the same database; then you only need to do one run.

@mhwombat Thank you that is a good suggestion, and yes they did mention their databases, but I have yet to see a paper that has followed this format. That is why it never crossed my mind.

Side comment: this kind of issues is one reason why journals should follow the lead taken by Ipol http://www.ipol.im/, a journal where papers are published alongside with their code implemented in a unified language, enabling readers to test and compare extensively.

@BenoîtKloeckner: "in a unified language"?

@O.R.Mapper: I meant that all codes are asked to be written in a given, fixed programming language, so  that it is implemented in the same way for all papers. This is probably more for the convenience of the publisher, who runs all published algorithms in it plate-form (you can go now and test any algorithm of any papers published by Ipol on any of the images on your hard drive), but it also make comparisons more legitimate.

@BenoîtKloeckner: Ah, yes, just wanted to make sure I interpreted that correctly. A useful restriction for the sake of comprehensibility across all works within one venue, and certainly a good idea in fields where such a restriction is possible.

Related: https://academia.stackexchange.com/questions/10247/why-are-cs-researchers-reluctant-to-share-code-and-what-techniques-can-i-use-to, https://academia.stackexchange.com/questions/96356/can-one-demand-to-see-code-used-to-generate-an-article/96358#96358

I'm had similar experiences, so I can relate to your frustration. One thing to bear in mind is that the authors may not have the source code available in any usable shape. One common scenario is that a junior member of the team did all the actual coding. And it's also relatively likely that that person now no longer works in academia, no longer has access to his code, and has little memory or interest in his former life. Depending on how desperate you are, you could try writing paper letters and sending them registered - they're a bit less likely to be ignored.

I'm doing my PhD in computer science
  This will definitely take way too long and in my opinion waste a lot
  of time

Well, that is what a PHD in CS in experimental algorithms and areas is all about. You must prepare your algorithm, implement it, implement previous works and compare your work with them. So, how much time it will take you it is of no interest to anyone else but you and your supervisor. So, this line of argument is naive.

One solution would be to email the authors and ask politely for their
  source code

Yes, but it not the only one. You could ask for their datasets and run your algorithm on their datasets, instead of making yet another dataset. Moreover, experimental algorithm communities have well-known benchmark instances and all related papers work on them for easy comparison of results. Why do you need to build yet another dataset? It is OK to use this extra dataset AFTER you tested your algorithm on those community benchmark instances. You could also send your datasets to your "competitors" and ask them to run their experiments on your datasets and just give you their results. Prepare you experiments relatively to older papers, notify them of your PC specs (and provide alternatives PC configuration  - you probably have different  PCs on your lab) and tell them to repeat all your suggested experiments on an PC close to your suggested specs.
If you like so much to share code, you can also send them the source code of yours, provide explanation how to compile it and use it and then let them run experiments on their PCs and give you the relative results to their work. I know that this thought probably never crossed your mind. Why? "They might steal my work, how do I know they will give me correct results, it is too much work to do so, I don't trust them with my src code". And now you know why people do not want to share their code.
But you also probably forgot the most easy way out of your problem. Let your supervisor contact the first author AND the rest of the authors. Unless you are an exceptional PHD student with many amazing papers you are practically Mr Nobody and people will easily brush off your requests. It is harder to do so to your supervisor (unless he is Mr Nobody as well). Usually people do not want to say NO to future reviewers, collaborators and respected members of the community. Also it is important to CC all paper authors. The first author (PHD student) might be protective of his code and hide your request from his supervisor. If you CC the supervisor,  he might be forced to share his code or at least reply.
Last but not least: Be nice when asking.

Thank you for your excellent answer. Yes, wastage of time comment was from my point of view. As I will have to implement their work that might take weeks or months just to get a result for comparison. This I wanted to avoid and that is why emailed the authors... Asking to send my dataset to them to test is a great idea, I will add this as an option in my future emails... Yes, I am paranoid about sharing my code as mine is unpublished, whereas theirs is published so I cannot steal their work which is already published... And yes, I will ask my supervisor. Thanks again for your detailed reply.

Note that sometimes implementing other people's ideas is beneficial, because you can then easily combine their approach with yours. In this sense, this initial "waste" of time can provide several benefits later on. If you manage to be the guy that actually knows how to implement all (or most  important) competing methods gives you a serious headstart later on, when other people try to catch up on you.

<<"I don't trust them with my src code". And now you know why people do not want to share their code.>>  That's kind of a weird concern given their papers are already published.

Reproducibility in computer science is an important area for improvement.  It is reasonable to expect authors to to make source code available for algorithms that they present.  I've heard that some journals and conferences are putting pressure on authors to make source code publicly available (although I haven't personally encountered that).
In my experience, most scientists do make their source code available.  Not doing so both casts serious doubt on the legitimacy of their result, and is counter to the normal premise of public-sphere science.  It's also pretty tough to to justify, since sharing source code has no cost associated to it.
Being a PhD in computer science is most assuredly not about re-implementing existing algorithms, except maybe for pedagogical reasons.  You're right that it's a waste of time.  There is simply no good reason to do it when the code could be hosted on github for free!
A good strategy is as follows.

Start with the corresponding author, or first author.  Tell them what you're doing, that you intend to cite their work, and that you'd like to benchmark your method against theirs.  Do be cordial, and feel free to tell them what you like about their work.  Most likely they're a cool person.
If they don't respond after a reasonable delay, say a week, send essentially the same email to the entire authors list, explain that you're having some trouble getting in contact with the corresponding author, and inquire about who is in the position to speak on behalf of the group.  This has yet to fail for me.
They should provide their source code at this point.  If they don't, it's fair game to inquire as to why not.  Since it's published work, there's sort of a premise that they should make it available except if there's something really making that a problem.  It's pretty fishy if they don't.  You can also remind them that you wouldn't want to make any mistake while implementing their work, so that the comparison is legitimate.

Don't worry about being a "nobody".  The idea that a researcher should only respond to high-status people is just ridiculous.  What you do need to be aware of, however, is that a prominent researcher can receive a lot of incoming communication.  If they're professional, they'll have set up triaging for that.  The best thing to do is make it easy for them to respond, and they will probably be pleased to help you, a student, which they once were.

Sometimes they are not happy to give source code (patenting/copyright reasons, or because of "dirty laundry code"), but ok with providing a binary. Offer that as an option.

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Finding and connecting with academic headhunters
As a senior in my field, but very unhappy in my current institution, I am eager to move. My high REF score/productivity and ongoing Impact mean, even before grants, I cost less to employ on a fractional Chair, such as I currently hold, than I bring in. But there is a limit to how many fishing conversations I can have with colleagues elsewhere without these getting back to my current employer. Plus it becomes generally unprofessional.
So I am looking to post with academic headhunters (I know they're relatively rare, but they are used, especially for this kind of post).
Google search reveals firms who are only interested in approaches by institutions.
What are effective strategies for finding and connecting, discreetly, with academic head hunters?

Well I'm not shopping for a job I'm asking about Headhunters' names. How or where else would you suggest I do so?

Please see https://academia.meta.stackexchange.com/questions/3657/why-was-my-question-put-on-hold-for-shopping; "shopping" refers to any question where you're looking for a specific product, service, company, etc.  I am afraid I don't have any other suggestions as to where to ask.

Actually, you are shopping for names. Any sort of shopping is discouraged here.

Don't people receive notifications of job offers from apps like LinkedIn ?

Are you looking for a job in administration? (Vice-Chancellor, Dean, Provost, etc.) I get the feeling that the sort of headhunters you've heard of are for those sorts of positions, not regular research/teaching faculty positions.

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Dealing with consulting agreements where NDA conflicts with research interests
I am a computer science doctoral student working on machine learning (ML) research. Meanwhile, a startup approached me to consult/advise them in areas related  to algorithms in ML. Needless to say a lot of work that I do as part of my research encompasses ML deeply.  They want me to sign a mutual non disclosure  agreement (NDA)/ non compete clause before i engage as an independent  consultant with them, while pursuing my program full-time. In this context, they know well that I will be pursuing my program for at least the next 3 years.
I have a few problems here.

The confidentiality information covers:

...techniques, know-how, processes, algorithms... related to current and future proposed products and services... and includes, without limitation, their respective information concerning research, experimental work, development, design details and specifications, engineering..."

I am worried about this part mostly. Most ML research uses some form of classification or clustering in various domains. Every other startup is mining some patterns that they may use to their advantage. The methods used are generally known in the ML community and published in existing literature. Can a startup claim that an "algorithm" (which already exists in the literature) was used by me in some form at a later point of time for work unrelated to that domain? Additionally, I intend to use or publish research methods developed as part of my doctoral research during its course or in future. Does "without limitation ...respective information concerning research, experimental work, development" restrict me from doing this i.e can the organization restrict me from publishing work done in my doctoral program by claiming that I was also working with them during this period, so they have a right to what i publish during this time?
Regarding confidential information:

"...if orally disclosed, designated as confidential at the time of disclosure and marked in writing as “confidential”."

Does this mean that anything said orally related to ML is considered confidential?
Non-Compete clause:

"...with a direct competitor of Company while engaged with Company and for thirty-six months following the termination or completion of this engagement..."

As an ML researcher, I will be working on ML in the future years to come. Asking me to stop working in ML for 36 months is equivalent to asking "don't work for 3 years". Additionally, the startup does work which is similar to the kind of work a lot of analytics/data science related firms do. Most of ML research broadly falls into pattern mining in some form which almost all organizations engage in. In this context, does 36 months not seem a bit unreasonable?
What exactly can i get them to write in the NDA which informs that they are aware of my research position and do not expect IP for my academic research?

Sounds like you need to talk to a lawyer.

IANAL and all but that non-compete clause seems pretty extreme.

An good example of requirements for such NDAs can be found here https://www.cl.cam.ac.uk/~mgk25/consulting.html

You are dealing with a legal document, and you are asking questions about legal language. The only way to get answers to your questions is to consult a legal expert. Any advice you receive here will necessarily be inferior to that dispensed by the legal expert.
Having said that, you're asking good questions, and during the negotiation part of the discussion you can and should discuss your concerns with a legal expert and with the company representatives. Negotiations are a normal part of any contract discussion. The document you have was written by their lawyers to provide his client—the company—with maximum legal protection, in their best interests. The job of your lawyer is to provide yourself with the same protection, in your best interests.
If you are concerned about the cost of hiring a lawyer, do the math; the total amount you expect to receive from the consulting should be significantly more than the cost of the lawyer, and the potential cost to you of not hiring a lawyer may be pretty large.
Regarding finding one, speak with the faculty in your department; chances are at least one of them has consulted in the past and can provide you with both advice and hopefully the name of a qualified lawyer.

+1 for consulting a lawyer in your case. IANAL, but I have some background in IP law. The agreement you are considering between you and the company may well have serious ramifications for your future activities and career. Yes, lawyers cost money. As eykanal said, they've got their lawyers to protect their IP. You need to be certain that any agreement you enter into will not constrain your future activities adversely. Find an IP lawyer, preferably one with experience in dealing with computer software.

I would add that 1) you must negotiate that 36 month no compete down to 12 months or less, it is unreasonable,

and 2) attempt to negotiate, written specifically in the contract that the assignment of IP to the company is strictly for specific machines developed by you, and the data, feature extraction, etc. specific to the problem for the company, and that all other general machine learning, and any algorithms or classification methods developed in the course of this work, are specifically excluded from the assignment of IP.  You will need a lawyer to be precise about this.  If you do not do 2), you will end up in big trouble with your thesis, with high (log) likelihood.

Non-disclosure documents are almost always trying to squeeze the employee. Here are a few specifics that I can glean from the snippets that you've posted.
I'm not a lawyer, but honestly I don't think you need a lawyer to interpret much of the language in an NDA.
ONE: The NDA
First, the NDA claiming that it covers processes and know-how relating ML methods refer to anything that you are working on related to current and future proposed products and services.
So let's say Company X is working on, let's say, movie recommendations and uses, for example, SVM (support vector machines) and collaborative filtering for the bulk of their recommendations. This does not mean that you can no longer talk about SVM and collaborative filtering with anyone - it DOES mean that you cannot talk about their particular implementation of SVM, you cannot tell people how they're doing collaborative filtering (ex: their features, their weights), you cannot mention what's in their databases and so forth. In fact, you probably can't tell people that the company uses SVM and collaborative filtering unless they tell you that you're allowed. If you develop some new technique of doing a movie recommender, you cannot tell people outside the company about it or publish it unless you get permission from the company. The key part of non-disclosure is that you basically need permission before you can talk about certain things, but common knowledge is common knowledge - it's not like the company can restrict you from talking about SVM and collaborative filtering. But if that's on their "super secrets" list of stuff, you better not go to a conference, give out your business card, and then say, "Well I know a lot about collaborative filtering and SVM".
Usually, "without limitation" DOES cover stuff that you work on outside of your work hours if it's directly relevant to the company. If there's a remote chance that your dissertation work and your publications might be inspired by, let's say, solving a company's problem or working with the company's data, then they actually do have the right to restrict you from disclosing your work without their permission, and may in fact claim copyright as well.
On the bright side, there are possible recourses for you. You can talk to them and ask them explicitly that you want to retain your copyright and that you want to reserve the right to publish about algorithms and so forth that you develop while you're there. You can promise to not disclose the company name and line of work. You can ensure that any papers you write go through their legal department so they can rubber-stamp it before delivery. These are things though that you want to ask about before you sign the NDA. Often, you CAN negotiate on terms like this, but it depends on their legal team.
TWO: Confidential
It seems to me that this is pretty clear. We've all taken formal logic, yes? That would mean that if something is orally disclosed to you, told to you that it's confidential, AND marked in writing as confidential, then you cannot talk about it. Unless they tell you, "Our implementation of SVM is confidential" and then point to the document that says, "The company's SVM implementation is confidential" then presumably you can talk about it.
That said, it seems like their lawyers made a mistake here, because you'd think it should be an 'OR' relationship here - "mentioned as confidential at time of disclosure OR mentioned in writing as confidential".
In any case, since SVM is basically public knowledge, most of what I mentioned under 1 would apply here. SVM and collaborative filtering and other stuff like that is public knowledge. However, don't say "Company X does SVM and collaborative filtering" in public.
THREE: Non-compete clauses
I can't really comment as well on this as I have no experience with non-compete clauses, but in some states they're not even legal (ex: California) and if they're phrased incorrectly to be unenforceable you might be off the hook.
I'd be more concerned about "who their main competitors are" rather than how long the agreement is. Such an agreement wouldn't prevent you from working in ML research, but it might prevent you from working at Netflix if your current company is in movie recommendations. Much of the time the non-complete clauses are made to prevent an employee from stealing corporate secrets and other implicit knowledge.
FOUR: Exceptions
Don't worry about where you'd put that stuff, you're not going to be writing the NDA.
You should bring all of your concerns with them though. The main thing is that you've brought it up with them and possibly written it down, maybe in an email, so that they can get their legal department to put it in the right location.
All of that said, I think your main concern is that "I can't talk about machine learning while working at this company." I'm 99% sure that isn't going to be the case. They don't care that you talk about general ML techniques or continue to do ML research, but will care if you're exposing corporate secrets, developing algorithms that might help their business with their data but not keeping it secret, or going to work for their competitors right after you finish with them.
Before hiring your own lawyer, I'd simply advise asking theirs about every clause in the NDA. That would save you some legal fees. If they are unable to answer, or if the answers aren't satisfactory, then you can consider getting your own lawyer to go through it.

This is a wonderful answer. The only thing I would add is that if you think anything might be interpreted in a way that could harm you, then add an addendum to the contract which states, in plain (not legal) English, what you believe you are signing (your statement about what you would and would not be able to do), and have the company sign that they agree with you. It doesn't hurt to have a lawyer review it but the law is much more accessible that many people think.

I think the main question is, even if you hire a lawyer to interpret a contract for you, what do you get out of it? You're out $100 and the lawyer will only tell you vague notes about what you can or can't talk (does the average lawyer know the difference between ML research at the University, and ML work at the company?) It's actually more productive to talk to the company, because presumably they WANT to hire you. The engineering team over there probably rolls their eyes at the NDA; their legal team at least has the power to change it!

Yes, for ONE he really needs to specifically draft language stating that the only IP assigned to the company and subject to the NDA are specific features, weights, implementations of machines, and data, then have a lawyer review it for proper legal language.

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How hard is it to get an academic position in Australia/New Zealand with a PhD from the US?
I am originally from India, currently a PhD student in Mathematics in the US. As such I don't have very many ties to the US and I was wondering whether it is common for PhDs from the US to get academic positions in Australia and New Zealand. I have seen some jobs postings on http://www.mathjobs.org/ advertising positions in Aus/NZ universities, but I am not sure how many US PhDs apply to them.

Are most faculty members in Aus/NZ universities 'homegrown', or is it fairly common to see PhD's from other countries? Is a US PhD the norm, an advantage, or a disadvantage when applying for an academic position in Aus/NZ?

US PhDs are more thorough (5+ yrs vs. 3-3.5 yrs).  I'd imagine this to be an advantage.

@Jase: this doesn't necessarily make a US PhD more thorough. The first two years are approximately equivalent to a masters degree in New Zealand or Australia, which most students do (or at least 'Honours', which is basically the first year of Masters) before their PhD. Additionally, I believe PhD students in the US often have to do more teaching than their counterparts in Aus and NZ.

It is very common for faculty members in Aus and NZ to have come from other parts of the world. They will look primarily at your publication record, responses to selection criteria and referee letters (selection criteria are an important and formal part of job application process in Australia, and are used instead of research and teaching statements used in the US). A PhD from a R1 university in the US will be considered equivalent to a PhD from an Australian university and an Ivy League PhD might be a small advantage, but less important than the other factors mentioned.

Also: you will probably have more publications than a recent PhD graduate from an Australian university, since Australian PhD degrees are shorter. This could put you at an advantage.

The proportion of "homegrown" to "...imported?" PhDs varies depending on your discipline, but at the science end of things (I'm in computer science, but know plenty of mathematicians and also majored in chemistry as an undergraduate) it's quite international. Apart from pathological cases (known "bad" universities, or otherwise extremely dubious universities), where you got your PhD is not particularly important. As Jeromy says in another answer, international experience is definitely viewed favourably though. My having done my doctorate overseas has definitely been a boon.
The real criteria are performance based; publications, teaching (especially awards or other recognition) and ability to bring in the grant money! (That last one in quite important, for better or worse). As a recent Doctorate, you'll mainly need to show that you can conduct quality research.
Just for some completely non-statistically-significant stats, my Australian undergrad. chemistry department had about 50% overseas PhDs, my CS department had more like 90% overseas PhDs and my maths department had about 50% too. At my current (Australian) department (CS), it's probably about 70-80% overseas PhDs (though that's a guesstimate at the moment), including me.
Of course the caveat is, again, this will change from department to department and university to university. Some like to only hire their own graduates, others will never hire their own graduates. Your best course is really to contact the academics offering the jobs, establish a bit of an informal relationship and find out what each position is looking for.

I know many academics in Australia who obtained their PhD in the United States. In general, I think that overseas experience is seen as a positive, whether it be an Australian going overseas to do a PhD or a PostDoc or a non-Australian  obtaining their PhD or PostDoc overseas. Some ranking systems even rate departments based on the number of international faculty members.
Of course, you still need to meet the job requirements. Thus, it is still going to help if you have a great publication track record, have studied or worked in a world-renowned university with world-renowned academics, and so on. Most Australian universities have a job listing site where you can subscribe to job alerts. Also, you would generally need to have good English language skills.

Your research publications and the quality of your research are more important than were you got your Ph.D. When recruiting for an academic position, the committee is generally looking for someone with an excellent research record. It can help if you went to a famous university, but if you went to a famous university and do not have good publications, it will not save you.


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How much experience should a teaching letter writer have with my teaching?
When applying for academic jobs in the US, one is often asked for a recommendation letter from someone who can attest to your teaching abilities.
How much experience should the letter-writer have with your teaching? Should they have observed you teach multiple times? (In my present postdoc I will teach 3 courses per academic year, should I be inviting potential teaching-letter-writers to visit each course? Or perhaps a selection of undergraduate/graduate courses/seminar talks?)
Are the answers to the above different for postdocs/tenure-track jobs? Within tenure-track jobs, are they different for research-focused versus teaching-focused jobs?

I am personally in mathematics. I am assuming the answers will not be too field-dependent (please correct me if I am mistaken), so I left it out of the main body of the question.

Hi Aru: you've asked many good questions...maybe too many at once?  I wonder whether you'd consider breaking down your question a bit.

hi @PeteL.Clark thanks for your comment, I would be happy to do so. Just to be clear, do you mean that I should state more specific questions in the body of this post, or break this into some number of distinct posts? (By 'post' I mean something that appears on the front page of the site.)

The latter: I think you have enough questions here for several, um, questions.

In a situation where "teaching matters", there are two significantly different tangible assessment types: student evaluations, and peer (or supervisor) evaluations, not to mention the more extreme sort of commercial sites which have the systemic problem that the commenters self-select, typically with skewing to negative, even ranting reviews.
The aggregate response in university-organized end-of-term student reviews is useful, not necessarily as a gauge of whether you're a good/effective teacher, but whether the students are "happy". For that matter, successfully generating no "complaints" during a term is some kind of success. This does matter.
Peer-evaluation (occurring not at pre-arranged times, but unplanned, yes), or evaluation by your director of undergrad studies in your department, is the closest to what hiring committees might care about. In particular, if you are doing what your peers or "boss" think you should, it doesn't matter whether the students love you or not... as long as they're not actually unhappy.
(Indeed, our goal surely isn't so much to make students "happy" in a superficial way, as to achieve certain pedagogical goals.)
The attributes relevant to undergrad teaching, especially lower-division, are essentially unrelated to seminar talks and even to graduate-level teaching, since the objectives (and the frame of mind of the audience) are invariably very different.
Edit: a "teaching letter" that merely reports that the student evaluations were positive, or that there were no complaints, is positive, but cannot count as a "strong" teaching letter, I think. This is a special case of the weakness of recommendation letters of any sort that merely repeat facts not known first-hand to the writer. First-hand information is better, and, further, lack of a first-hand-information letter-writer is not a good thing...

How much experience should the letter-writer have with your teaching?
  Should they have observed you teach multiple times?

I don't think there is a "right" answer here, but there are a number of educated guesses that represent sensible approaches. I will list a few points that common sense suggests, as a starting point.
It makes sense that the person providing a letter should be familiar with your teaching at least "on paper." In other words this can be someone who has observed your teaching at least a couple of times. (I don't think it is critical that the observer has sat in on all the classes you teach, but maybe a couple sessions in one or more classes, to have some general idea of how you are doing. Chances are these were representative examples.) OR, it could be someone (like dept chair or your PI/postdoc advisor) who can be reasonably expected to have access to your end-of-semester course evaluations and has some decision-making capacity with regard to your teaching assignments.

should I be inviting potential teaching-letter-writers to visit each
  course? Or perhaps a selection of undergraduate/graduate
  courses/seminar talks?

I think both are fine ideas. Keep in mind the availability of those you are asking, so as not to overburden them with these requests. Sometimes once sit-in might be enough for an experienced faculty member to form a reasonably accurate judgment of your capacity for teaching. Kudos to you if you do not 'orchestrate' the specific class they sit in on, but invite them to drop by 'any time' on any class (except exam time). This is mostly for your own sake, so you can hold yourself to a higher standard overall across your classes. The confidence required to extend such an invitation may not go unnoticed as well.

Are the answers to the above different for postdocs/tenure-track jobs?
  Within tenure-track jobs, are they different for research-focused versus teaching-focused jobs?

Seems a bit like splitting hairs here...I believe any sensible approach should be sufficient across all of your purposes. The only caveat would be that common sense suggests that deeper familiarity with your teaching will allow the letter writer to write something more coherent about your teaching than the collection of generalities that may be the limit for someone only casually (e.g. indirectly) familiar with your teaching.
(Side note: There are more public though less formal records compared to course evaluations, like RateMyProfessors.com. Not the most authoritative resource on objective evaluation of teaching, but see how you are doing there, just in case.)
Finally, teaching simply doesn't matter as much when applying for research-focused jobs. If your core responsibility will be to drum up grant funding, worry about that in your application, and don't worry so much about your teaching record. This may not be universally the case, but should serve as a reasonable rule of thumb.
Good luck!


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When is it okay to ask your advisor solution to a technical problem?
For example, if (hypothetically speaking) I am stuck on proving a theorem, is it okay to ask my academic advisor some help for next step? My approach has been, "this is what I have tried, I am stuck here...can you point out how I can continue". But the amount of time that it takes the professor to reply is stressing me out, I am afraid that he is getting exasperated at my question.
What makes thing a bit worse is that the prof says flat out he likes people who are able to solve problems independently. But he also has a reputation of being a fast replier to student emails regarding problems arising in his course. I wonder what he expects of me.
So what is considered appropriate to ask your advisor without pushing him to the limit of having to solve the problem himself. Ultimately I am worried about looking totally incompetent. Is there some way for me to not appear totally incompetent?

You should not worry whether you look incompetent. At the end, it is unimportant. You should worry whether you are competent --- if professor always can answer your questions quickly, then you probably getting stuck at relatively easy bits. You should ask yourself and your advisor what you can read, which problem sets you can practice on, etc, so that you can learn the skills that you lack.

I'd describe this situation as a research problem as opposed to technical problem. To me, technical problems are instruments not working, lack of tools (and importantly, money to buy tools and supplies - which would always require asking the supervisor).

Why not ask him what he expects of you?

Your approach to asking -- "this is what I have tried, I am stuck here...can you point out how I can continue?" -- is the right one. Without knowing how difficult of a problem you have gotten stuck on, and how often you ask for help, it is very hard for us to judge how your advisor will interpret your request.
That said, in general I very much appreciate it when my graduate students and postdocs let me know when they get stuck on some step of a research project. My students and I are collaborators after all, and if I can help them get going again, or alternatively if I can recognize that we've been heading down a dead-end, this is very much to everyone's benefit.
Of course, they should not be coming to me with trivial problems: "I can't get this expression to format properly in LaTeX" or "I don't know how to compute the Jacobian matrix for this function", nor would I want to get these requests on a daily basis. But if a competent student has made a serious effort to solve a problem and is still stuck, I'd like to know about it and to help if at all possible.

+1  Moreover, this is the right approach when asking anyone for help with a problem, not just your advisor.

First you should ensure that your question is not trivial (as @Corvus noted).
Are there other graduate students in your group? Talk to them. Bounce ideas off them first. There may be senior PhD students or the like in your department who may be excellent resources for certain types of material.
When you have exhausted some of these avenues, you can and should discuss the roadblock that you have with your advisor. It is quite possible that your advisor may also need time to digest the question and provide an answer or provide some direction. Remember that your advisor is your collaborator and that you are tackling a research question and so others may be as stumped as you are. Even if you believe your advisor is extremely capable you should bear in mind that faculty members have so many tasks to attend to that the fraction of time available to think deeply about your question is quite limited. This may be another reason for delayed responses. A PhD student may have a course or two to tackle but will have -- or is expected to have -- sufficient time to think deeply about a problem.
One more possibility is to discuss your problem with another faculty member in your department who may not be working on the same problem but may have the relevant background to quickly set you on the right path.
A professor responding quickly to questions in a course is quite different because she or he is already an expert on the material, likely set the question or has answered it in the past. So a swift response to student doubts in those cases does not contradict slower responses to open questions.

To offer perhaps a different perspective here, I wouldn't have hesitated to discuss something like this. Yours likes people who are able to solve their own problems. I'd perhaps pose the question though, that perhaps he also values those who know their own limitations and seek advice from others.
As the other answers stated, it's always good to talk to other students or post-docs. This may be for specific advice, or simply as a form of "rubber duck programming" - there is significant learning and new understanding by explaining something in fundamental terms to a metaphorical (or physical) rubber duck sat in your desk. If your colleagues are not experts in the field, even discussing the problem in broad terms may help you spot something you didn't spot before.
To give an example, I once was stuck in knots, trying to work out a complex concept in some code I was writing. I ended up discussing the problem in fundamental terms with my coworkers in the office. The process of explaining it to them (non experts in the topic) made me really think about the problem I was facing and its context. That led me to have the proverbial brainwave, and find a new angle of approach to the problem I hadn't considered.
In saying that, as I said earlier, I never hesitated to discuss things with my advisor. In fact, we would generally try to talk for at least half an hour per day. Of course that wasn't all seeking technical advice, rather dealing with ongoing business and updating each other on any progress or interesting ideas or discoveries. Obviously this depends on your advisor, but in my experience, advisors value independence, but also recognising your own limitations. I would rather a student I'm supervising came with a problem, than struggled and made no progress for weeks or months.
You asked how to avoid appearing "totally incompetent". What I advise is that you prepare a brief summary of what you've attempted. Be able to concisely explain the problem, and your initial analysis of how to solve it. Then be able to state the problem you're experiencing, and what you've tried to work around it. Did you refer to any other works or books (if so, mention this)? Putting a bit of effort into the question shows that you have put the work in, and understand the problem, but need some advice. Don't expect your advisor to immediately solve it, but perhaps they will give a few pointers or ideas. The first few words I mutter after being posed with a problem are often scribbled down quickly by students, who then go away to decipher them and try them out - often the initial thoughts from someone uninvolved with the problem help to solve it or offer a new insight or way of thinking.
I would add though that often it takes me a while to look through a complex problem. And I am often bad at replying to emails when my initial reaction is to delve straight into the problem! Replying to class-related questions is typically much easier (they are generally based on established theory and can be answered with reference to slides, notes or books. Failing that, the explanation is usually familiar). For ongoing, leading edge research, that's obviously not possible. Don't panic - in the cutting edge of research, even the most experienced professor doesn't know the answer immediately. Otherwise it wouldn't be the cutting edge!


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Under what circumstances can the university council withhold Ph.D. degree?
This a case 28 years ago where the defense committee approved the dissertation and recommended granting the degree. The department council and the college council both approved granting the Doctoral degree to the candidate. However, the university council did not approve awarding the degree and did not give formal reasons to the lower councils.

What are the norms in north American universities? Under what circumstances can the university council withhold (or deny granting the Doctoral degree) Ph.D. degree to a candidate?

I am not allowed to disclose the university name. The university is in the Middle East.

This a famous case 28 years ago where the defense committee approved the dissertation and recommended granting the degree. What case is this?

I know this is very weird but it happened.

I believe that it happened, but it would be great to know what the famous case is, since it is apparently not famous in my field or the universities I have been affiliated with.

If you cannot give the name or more information, how can we compare what happened there with what happens in other universities?

@Alexandros I am not allowed to disclose the university name. I am not interested in a comparison of two systems . The university is in the Middle East.

I think we are having a language issue - if the case is famous, it can be mentioned specifically. If it isn't, then it's confusing and you should probably just remove all reference to it as distracting.

@BrianDHall Removed famous since it is not known in North America.

The system you / they are operating under with multiple approvals needed is not normal in North America. The normal case is that the committee makes the decision, and there is no further consideration. Someone can lodge a complaint which may lead to an investigation by the relevant university-level governing body ("The Graduate School"), which could lead to overturning a committee approval, if it was found that there was something seriously wrong. The final "decision" is usually made by an even higher body, often called "The Trustees", but that is normally pro forma -- except, again, if there is something seriously wrong with the case. Of course there may be North American universities that are more than two sd's from the norm.
By "seriously wrong", I mean that there was proof of academic misconduct, or possibly a wanton abandonment of academic standards by the committee.


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Search all Theses online
Is there a way to search all openly published theses online?
Maybe there is a way for Google Scholar to ignore other types of articles?
I am aware of SCOPUS and Web of Knowledge, but unfortunately I do not have access to these services.
Edit: I talked to my librarian and we found a service called EThOS and additionally a service called openthesis.  Openthesis requires people to upload submissions, which would cover nowhere near as many as Google has indexed.  EthOS is for the UK only.

Why would you want to search ALL theses? It's kind of like saying, "Is there a way to search all magazines online?"

@Irwin forgive me, I don't understand what you mean.  I would like to limit to only theses.  From my understanding Google Scholar indexes all types of articles, but I am looking to only search theses.

What sort of information are you looking for?  If you want to learn something, I'm not sure why you would only want to learn it from a thesis (as opposed to journal papers covering the same material), and the same holds for finding out whether an idea is already known.  If you are looking for a specific thesis, then that's a different question from searching through all theses.  If what you are trying to find out is about theses specifically (e.g., what is the length of an average history thesis), then it's enough to have a representative sample rather than a complete list.

So how did your university librarian answer this question?  (You did ask your librarian, didn't you?)

What @Irwin was hinting at was that you would probably want to narrow it by subject/field. If you are looking for a thesis in anthropology, you don't want a service/engine that will also peruse/return theses in molecular biology

+1 @BenNorris In my undergrad days I once did a ProQuest search with relatively poorly chosen keywords (for lack of knowing any better). I was trying to do some research on Baudelaire, and ended up with a large number of theses in biology and allied fields.

@BenNorris couldn't you simply use keywords to get around this issue?  Ultimately, It will be a lot easier to narrow my searches then it will be for me to broaden them.

@Liam I don't mean to disappoint you. The question Use Google scholar only for open access journals would tell you that you'll have hard time to find only open access articles. Not to mention theses.

The only thing I can think of given the lack of other details is this They claim to be "the world's most comprehensive collection of dissertations and theses." While that is not "ALL", it certainly is "MOST"?

Check to see the list of sites that are comprehensive: https://www.netvibes.com/ircnigeria#FREE_Virtual_Libraries
One of them, Global ETD Search http://search.ndltd.org/ as at today has 5,382,984 electronic theses and dissertations contained in the NDLTD archive

all_licenses: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


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Is there something between auditing and taking for credit?
Is there a system in place that is in between auditing a course and taking it for credit?
I have audited a course before and I didn't learn enough material to prepare for the actual course.

So your intent is to audit the course, then take it for credit? Seems like you should just take it and put the effort into passing it for real.

@JonCuster for those with disabilities this is impractical.  For many students it takes multiple tries which institutions don't allow.

Certain courses, such as organic chemistry, are known for taking several tries for various students. Have you approached the proper office for disability assistance? But, ultimately, if you need that course, you need to put in the time to prepare for it.

@William If you have disabilities, you should work with the institution's disability office (hopefully it has one...) to get proper accommodations. Taking a course multiple times by auditing it the first time does not seem like an ideal approach to me, especially if you pay the same rate for auditing a class as taking it "for real."

It would help to specify region/country here, as in some places you can just retake exams until you pass with no penalty, so there the answer is just "take the course/exams until you pass". If not, you could look to your institution's retake policies, as some in the US will let you retake if you have a D or below multiple times and they will not penalize your GPA as they only report the final taken grade. Other institutions have no such leeway and will report every grade earned and include it in the GPA; that provides much less flexibility. But this is all very locale-dependent.

Now that you have indicated you are in the US, in the two institutions I was a student at in the US you were permitted to retake courses. Both versions would show up on your transcript, but only the most recent grade was counted in your GPA. Additionally, if you are in the US your institution almost definitely has a disability office, you should consult them about all of this, they will be much more helpful than anyone here can be.

How much you learn is more dependent on what effort you actually put in than on your formal registration status.  For instance, if you audit the course, attend all the classes, take notes, study and review the material, complete all the assignments on your own, and (if possible) meet with the instructor occasionally to ask questions and check your understanding, you should be able to learn just as much as if you were taking the course for credit.

@NateEldredge How much you learn is dependent on a lot of things, not least of which is the course structure and the quality of the instruction.

@ElizabethHenning: Certainly.  I didn't mean that as an exhaustive list, and I was focusing on aspects that are the student's decision.

This depends on your institution, so you will have to ask someone there, a general answer is not possible.
My undergrad institution allowed for taking some courses (specifically, those not part of the specific requirements towards your degree) as pass/fail rather than graded, which meant if you scored at least a C you got credit and if you scored worse than a C you didn't, and the course wasn't included in your GPA.
However, auditing a course typically gives you the same access to course materials as taking it for credit; the opportunity to learn should be the same however course credit is assigned. Auditing is not typically a way to prepare for a course, but rather for self-enrichment and perhaps to learn material outside your area of expertise without being evaluated to test your interests.

edit: The OP has since indicated that their reason for auditing these classes was that they hoped to prepare ahead of taking the course for a grade, due to disability they experience. I would recommend consulting with the institution's disability office to get proper accommodations rather than using the audit or pass/fail system directly.

I don't think it's entirely fair to assume that this is an issue of personal motivation. Courses tend to come in a one-size-fits-all structure, which can put many students, especially those with disabilities, at a significant disadvantage. I would be more inclined to place the blame with the institution for not requiring courses to be structured with greater adaptability to a variety of student learning needs.

@ElizabethHenning I'll edit that out. I wrote that before the student mentioned a disability; at the time, it seemed like they were blaming auditing the course (i.e., not having responsibility for a grade for the course) for not getting enough out of it. I agree with you that there may be other structural issues with the course(s) to blame, but those cannot be addressed by the difference between auditing and taking a course for credit, and the next step is still to consult the disability office.


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How to survive as a postdoc with unsupportive mentor and team
I am at the end of 2nd year postdoc at a famous CS lab in the US. I have changed my research area (but related) that I worked for my PhD.
1) My current project and the lab focus are different than what I was working on earlier in academia. Moreover, the problem I'm working solely on is widely-accepted as hard to tackle. I have some preliminary results but not enough to publish a paper. An alternate (inferior) approach at some other university (with grad students) took almost 4 years to run. I'm being constantly told that I am unable to progress as they expected. This is de-motivating me to hold on to addressing this problem. With no visible publication yet, peers and other colleagues are assuming that I'm not worth researchy material. How do I take these criticisms constructively and stay focussed and solve the problem.
2) From my PhD, I had 4 publications in top rated conferences in my field. There is another group in my own team who work in the same area. When approached for collaboration with them so that I can use my expertise in the current projects, they do not include me in any work. What puzzles me is that why do they not understand (or why am I unable to convince them) that I hold expertise in that area and could very well contribute to their work. They are happy to take a novice with little-to-no knowledge of the field, but do not want me. They had few publications this year, where I could have very well been one of the co-authors. Due to points (1) and (2) I have no single publication; neither as a main author in the new research area nor as a co-author in my area of expertise, which makes it very hard to proceed to next level of career. I spoke to a senior scientist about this, he replied that most of the postdocs and few staff are so insecure of funding, that they do not want anyone else to be included in their close-knitted group. How do I overcome this?
3) There are couple of postdocs in my team each with their own mentor. My mentor is fairly junior having recently converted to scientist, himself being a postdoc for few years. Other mentors are more senior to my mentor. I feel that my peer postdocs are being guided and mentored very nicely; they are invited to talk to any visiting scientists, work with summer students. My mentor has 3-4 summer students every year; but does not want to me collaborate with them. This is reducing the scope of any joint publications with them, while others have atleast 2-4 papers per year with the summer students.
4) I am not gaining any visibility in terms of invitations to serve for program committee or workshops, where my peer postdocs have bunch of them in hand, owing to the support from their mentors. All postdocs have more or less the same number of publications in similar venues. I agree that it has to do more with networking, but due to the nature of work, I hardly get time to attend any networking opportunities barring 1-2 workshops a year. This is not helping me boost my research career.
I want to get feedback on how do I boost my postdoc career and survive here if at all I want to. I personally think my mentor is limiting the options that I have to improve networking skills, collaborations across projects. I feel so isolated and dejected. I am willing to learn any skills that I may be lacking.
Thanks,
K

Two years as a postdoc at a seemingly crowded place? Time to go somewhere else?

@Karl. If only there're more postdoc jobs in every region..

I am actually in a situation that's similar to yours in a lot of respects (i.e. at the end of a postdoc and not that much to show for it due to lack of collaboration with my team for various reasons). So I'll give you some advice I have been trying to apply myself - although I haven't quite succeeded spectacularly so take it with a grain of salt.

It's a systemic problem. This is not practical advice on what to do, but emotionally, you need to try and kind of self-distance yourself from this situation to realize that academia does not encourage researchers - after their PhDs and before tenure - to go out on a lim exploring something deep that doesn't show immediate results. There are no mechanisms for consideration of effort and risk and potential impact of success, while an epsilon-improvement on the state of the art in what's fashionable is usually a sure-fire success.

Finding collaborators is job #1. Unless you can churn out award-winning work yourself, you absolutely must find collaborators. Maybe that means quitting the group, eventually. In the mean time, be very very active in contacting people who do work you feel you could build on or collaborate in, introducing yourself, talking about your plans etc. Possibly also out of academia if that's relevant.

Try to bargain with your mentor You're expecting your mentor to behave in certain ways, but they arent doing so. You should have (and possibly still can) talk it out with him, in the sense of realizing why their behavior.

If you can, try to get direct access to students You mentioned trying to work with tenured faculty's students. If you could somehow get in touch with prospective students yourself, that would be a bypass. Proposing to teach a workshop or proper course, or to co-teach something, or to offer a "lab project" course, or to give a guided tour of the lab's activities, could help. Of course, that has a cost in terms of effort.

Take the time/effort to also pick more low-hanging fruit Try to either branch out to a close/related subject, or work on a problem in your main subject of interest, which you think is not very significant - i.e. probably the opposite of your intuition regarding how to choose what to work on. While this would not yield a great publication, it could yield something publishable and opportunities to talk to people and make connections. It would also make it not appear like you're unable to produce anything in the bottom-line sense.

Explore collaborations with your PhD advisor and his/her group. You did well during your Ph.D; I assume the people around you did not all die in a car crash... talk to them, especially your old advisor if you're on good speaking terms. In fact, you could even ask for their advice on your predicament (that's orthogonal to suggesting collaboration).

Explore opportunities for funding. While this requires collaboration with a more well-established academic figure, you should still give it a try. In fact, it might be an opportunity to bypass your own mentor if s/he is not interested in helping, by talking to the more senior / most senior people in the lab. If you manage to secure funding, that would almost be like getting students; it would mean your lab and even your mentor would be more committed to promoting the research you're doing; and it's an important thing to have on your CV.

Note: These suggestions are not comprehensive and are not in any particular order.

Thanks @einpokulam. These comments are helpful. I was wondering if putting these efforts in this lab are worthy, given the non-inclusive nature of the team.

@kris: That is something I would not presume to speculate about without knowing you and/or the lab personally.


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General structure of Research Statement (applying for faculty position)
I'm going to apply for assistant professor positions (in theoretical computer science) soon, and I'm trying to get a feeling for how to write a good research statement.

Should it contain a detailed overview of my (recent?) publications?
If the answer to 1 is yes, should I highlight my specific contributions in multi-author papers - as opposed to "we proved this and that..." ?
If the answer to 1 is yes, I must list the references here that I'm mentioning, which are also stated (in the full list of publications) in my CV, right?
Assuming there's no page limit, what's an appropriate length for a research statement?

My current plan is to group my work into topics and then, for each topic, provide a short overview of the respective papers ("What I've done so far") and some outlook on some future work ("What I would like to do").

I would have more outlook for future work, and try to provide a coherent, long term theme under/most which all of your work can be described.

Should it contain a detailed overview of my (recent?) publications?

NO.  It should contain a detailed overview of your research program, including both your past accomplishments and your future plans/vision.  Of course you have to describe your published results in technical detail, but as part of a larger narrative, not as stand-alone pieces.  Focus on the big picture, not on the tiny technical details.  Remember that your audience is not just other theoretical computer scientists.

If the answer to 1 is yes, should I highlight my specific contributions in multi-author papers - as opposed to "we proved this and that..." ?

NO.  "My coauthors and I proved..." is fine.  The public dogma in theoretical computer science is that in every paper, each of the authors contributed 100% of the work, which is why they are listed alphabetically.  You own any paper that has your name on it.  Your narrative will naturally focus on the parts of the paper that you are the most proud of, which are usually the parts that you worked on the most.
Of course, if you're writing papers with your advisor or other more senior coauthors, there is a natural tendency for people to wonder if your aren't really just riding their coattails.  This is why you need a larger narrative in your statement—to convince the reader that you understand your results at a deeper level than someone who merely read the papers.  This is also why you have papers with different sets of coauthors—so that the common thread through your work stands out as your contribution.  In particular, you have at least one paper without your advisor.  Right?

If the answer to 1 is yes, I must list the references here that I'm mentioning, which are also stated (in the full list of publications) in my CV, right?

The approach I always recommend is to treat your CV as your bibliography, and to include a footnote like "Numbered references indicate papers listed in my CV."  Of course, this means that your research statement never cites anyone else's work, except in broad narrative strokes, but for a brief document intended to sell your research program, I think that's appropriate.

Assuming there's no page limit, what's an appropriate length for a research statement?

Aim for three pages.  Less than two is too short.  More than four is too long.
That may not seem like a lot of space, but that actually works in your favor.  You want to give the impression that you've done just gobs of really amazingly cool stuff, but dammit there just isn't room to write about everything.

As a note for those reading these questions who hail from other disciplines: the length of the research statement may vary. In my (mechanical engineering) department, for instance, job postings state that research statements are expected to be five pages long. The length should follow the requirements of the posting, or the norm of your field (whichever is more specific).

"for people to wonder if your aren't really just riding their coattails" which is fascinating it itself. With some senior researchers writing 10+ papers with different members of their team in one year. It would seem so much more obvious that all the real work (i.e., coming up with the results) is done by the less senior ones... but I guess, as always it depends on both sides.


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How to submit 'teaching evaluations' for a job application?
Some jobs ask you to submit 'teaching evaluations'. Assuming the school doesn't have any preference for how I submit the materials, my issue is that I literally have hundreds of teaching evaluations - If I just send them all I know no one is going to look through them all, but if I do any sort of condensing I feel as though I will be clearly cherry picking the good comments. Any suggestions for making the most out of these materials in a job application?

I don't think a modicum of cherry-picking is a bad thing in this regard.  What you need to send is a set of teaching evaluations that describes what is significant about your teaching -- the

Great teacher!

comments aren't particularly worth it, but the

Dr. X constantly provided clear examples of the material, and it made the difficult topics more concrete.

samples can provide the insight that will be helpful to a hiring committee.
The committee is trying to get a feel for why you are a good teacher (be that the case), and that's why they want the evaluations.  I have provided bulleted lists of evaluation comments, but I have also provided a link to all of my comments from multiple classes.  The evaluation website at the university where I taught recently actually provided a statistical breakdown of the survey questions on each evaluation topic, so I was able to highlight the statistical takeaways from the surveys.

First, in most cases you have summary pages that give your overall statistics and even compare you to other teachers in the department. By all means, submit those (juts scan them all into a single PDF). Those are not cherry-picking in any way, so that would remove your main concern. Second, on the top of it, sift through the hundreds you have to choose the most meaningful and nice comments and scan 10-15 of them (you shouldn't be shy and afraid to show your best in your application: after all, if you tell me that you always dress as neatly and behave as nicely as you do on your interview day, I'll just laugh). That should be more than enough for any hiring committee member unless he has a strong prejudice against you for some reason.


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Channels for applying for faculty positions
I am a postdoc in engineering at a large US university and am planning on applying for tenure-track faculty positions this fall.
I understand that the nature of applying for TT faculty positions varies greatly depending on the field. I am inquiring mainly about engineering schools and business schools (specifically operations research departments).
My general question is: is there an organized procedure for how TT faculty openings are disseminated through the community?
In my limited search so far, I have not seen much online in terms of job postings. The postings are either outdated or very sparse. Furthermore, there is no indication on university websites if the department is hiring or not.
Related thoughts/concerns: Is it acceptable to send an application to a department when there is no job posting? Are there more effective channels for applying: i.e., give a talk in the department and inform the head that I am interested in applying? Leverage connections to contact someone high up in the department?
Perhaps the lack of structure in the job hiring process is inherent or by design. Any guidance on the procedure (for engineering and/or operations research departments) would be greatly appreciated.

Some fields have one or two dominant professional organizations with a publication in which most jobs are posted. In computing we have ACM and IEEE. Perhaps your field has something similar.

You should talk to your advisors about this question and job search in general. This includes both your doctoral advisor, and your postdoc mentor if you have one.

Another aspect to keep in mind is timing.  It is now July 2019, and most US universities have probably not yet posted job openings for Fall 2020 (though again this can vary by field).  They may not even be certain yet whether they have an opening - there are many levels of approval needed to start a tenure-track search, even to fill an existing line.  So it's also possible you are looking in the right places but it's just too early.  In my field (math), jobs are usually posted in August or September, with an application deadline of November or December.

I don't think you'll find one web site or publication which is dominant in the broad area of OR (which lives variously in business schools, math departments, and industrial engineering departments.)  One useful site is the INFORMS careers web site at: https://connect.informs.org/careercenter/home

Although it's possible that you might be able to find a short term visiting position through word of mouth or having sent an unsolicited email, you can expect that any permanent tenure track position will be nationally advertised.

@Buffy For computer science, I would suggest CRA long before either ACM or IEEE.

Ah, yes, @JeffE, of course.


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How much detail to include for an award listed on a CV
I would like to have a section titled 'Awards/Honors' in my CV and I am confused about how much detail to include for the items in this section. Here are some formats and levels of detail I am considering:

Harry Potter scholarship.
Hogwarts school of Witchcraft and Wizardry, Harry Potter scholarship.
Hogwarts school of Witchcraft and Wizardry, Harry Potter scholarship: awarded to one student every year for demonstrated excellence in horcrux-gathering.

For certain things, I feel like the first does not include enough context, beyond some very well-known things (such as a Fulbright or Goldwater, neither of which I have received). For some particular names I have in mind the second looks pretty clunky and does not always fit on a single line. The third option is even clunkier, and might be perceived as an attempt to add fluff to inflate the CV. I am personally leaning towards the second option, but I don't know that it adds much value beyond the first option.
Is there an accepted way to list awards/scholarships? Should I even be listing them at all?
Some context. I am a PhD student in Mathematics and I will be on the academic job market this coming year. I am currently based in the US and intend to apply to jobs here as well as internationally if I find any that are interesting. I am wondering both about the CV I keep that lives on my professional website and the one I hope to send as part of my job applications.

Edited to add: The first couple of answers suggest that one might choose the format/level of detail based on the type/prestige of award. If I were reading a CV and came across inconsistent formatting within a section, I would find it quite jarring. Is this something that only worries someone mildly-OCD such as myself (I notice things like en-dashes and em-dashes) and therefore perhaps to not be worried about, or should I be careful about such things (e.g. consistency of formatting) when creating a CV?

I will disagree with Dan C's answer above and state that you should only be choosing between options 2 and 3. At the very minimum, you want to indicate who gave you the award. Otherwise, it's not all that valuable to the reviewer of your CV, as they may not know whether an award is a big deal or not. If it's a major award, I'd default to option 3 if it's "non-obvious" how it works.
So, in general, I'd opt for option number 2, unless there's some specific information that needs to be shared, in which case I'd go for number 3.

The amount of detail you give should be proportional to the award's prestige.  So for example,

If you were recognized as an "excellent" teacher, among a list of 100s at your university, that's worth mentioning, but it gets formatted as option 1.
If you won a best student paper award, that probably gets option 2.
If you won "best PhD thesis in your department" from a department with more than say 10 graduates each year, that might merit option 3, although it's likely to fit easily in format 2.
If you won a prize from a professional society (awarded to very few each year), that might merit option 3.

+1, but if an award is worth mentioning, it's worth mentioning who gave it to you, so IMHO no option 1.

I would go so far as to give the opposite of Dan C's advice: the more prestigious the award, the less detail you need to provide.
If you won the NSF fellowship or the Hertz, or got best paper at your national conference, everyone will understand what the award is and its significance, and belaboring the point has the risk of looking desperate or inexperienced.
On the other had, if you won your department's annual [famous former faculty] Memorial Award for Excellence in Teaching, the award is still worth listing and you should include at least that much information on the CV. Assume nobody is going to take the time to Google your awards.
I would say, as my rule of thumb, that each award should fit on one line. If explaining an award's significance requires more than one line, that is a red flag that perhaps the award is not pulling its weight. Understating your accomplishments and aggressive mediocrity will both kill your chances in the job market, but in my opinion the latter is the most dangerous of the two.

You got good answers. I just want to add that it is usually a good idea to list the relevant year(s). I typically use this format:
Mickey Mouse Prize. Institute of Advanced Cartoons. 2010. Extra comments if needed.


text:
Can non-teaching staff write teaching recommendation letters for academic jobs?
When applying for academic jobs in the US, one is often asked for a recommendation letter from someone who can attest to your teaching abilities. Suppose someone has been involved in various workshops, programs, discussion groups, etc. about pedagogy through a Center for Teaching Excellence (or a comparable office) as a graduate student or postdoc; is it acceptable for a non-teaching staff member from this center, who has facilitated such activities, to write a teaching recommendation letter for academic jobs? In particular, how are such letters perceived by hiring committees?
Edited to clarify: I was envisioning that such a letter would be in addition to a teaching letter written by a faculty member in one's department.

As long as the non-teaching staff has good academic background, it is alright, I think.

I would view the letter favorably if the letter writer made it clear that they had observed the candidate's teaching.
I've seen some TA training programs where the TA's are observed in the classroom and get formal evaluations by someone involved in the training program.  A letter of recommendation from such a person would be quite valuable from my point of view (and assuming that the letter was positive this would be helpful to the candidate.)
On the other hand, if the person that you're considering is just a faculty development specialist who runs workshops that you've attended and hasn't directly observed your teaching, then such a letter would be much less useful (read useless) to me.

I agree that a TA observation letter would be interesting to the hiring committee, but the question is whether it is beneficial for the candidate to add it. If everyone else has glowing letters from professors they TA-ed or co-taught with, and you have that and also a really detailed classroom observation letter, does it help or hurt you in comparison?

The really detailed classroom observation letter would be helpful to me since I care about teaching.  In most faculty searches teaching is actually an important factor, but there are certainly some searches where the committee doesn't care about much except research.  In those situations, this kind of letter could be unhelpful (and might even be a negative if the committee thinks the candidate is too oriented towards teaching.)

I understand that it will be helpful to you, the question here is whether it will be helpful to the candidate. :)

In my opinion, for searches that I am involved in, having a positive letter of recommendation of this sort would raise my evaluation of that candidate's teaching.

However, as @mxmxmx alludes to in their answer, even if this person has observed your teaching so that they can write a useful letter, you should also get a letter from someone in your department (who has also observed your teaching recently).

Another important factor to consider is whether the person in question understands the conventions of academic letter writing.  The one time I have looked at a letter written by person in this situation, it was horrible.  I'm sure that person was especially incompetent (there were an embarassing number of typos, they had obviously cut and pasted from other letters, they wrote a lot of things that made no sense, etc.), but it made me very wary of such letters in the future.  I'll also say, from my experience in hiring at research universities that two teaching letters would look a little weird.  I think mxmxmx overstates things a little: while a lot of professors at research universities are essentially indifferent to a candidate's teaching, most recognize that it will be good for the department to have better teachers.  However, it is true that they're more concerned about avoiding disasters than separating good teachers from great, and most wouldn't seriously consider compromising on research quality in order to get a better teacher.
One thing you might consider: ask the non-academic staff member to write an more informal summary of their interaction with you, observing your teaching, etc., and have them send it to the faculty member writing your teaching letter.  That way, they can quote from it or use it for material, without having a separate letter.

I think we are basically in agreement. "most recognize that it will be good for the department to have better teachers" plus "most wouldn't seriously consider compromising on research quality in order to get a better teacher" is equivalent to "They just want to make sure you will not be a disaster in the classroom". :)

I think that such a letter would give a mixed impression, depending on the personalities of the people on the hiring committee and the priorities of the institution.
On the one hand, it could be viewed very favorably indeed. Being an active participant in such a workshops would signal your dedication to quality teaching, and perhaps this staff member could write a very moving and positive letter.
On the other hand, it could be viewed unfavorably. I think that some faculty members, especially at research-oriented schools, might have an instinctive distrust for this kind of organizationalism. Moreover, an active interest in pedagogy doesn't necessarily imply that you're actually a good teacher in the classroom.
Overall, I would recommend in favor of obtaining such a letter, especially if you are targeting jobs which prioritize teaching. However, you might consider getting a second teaching letter from someone in your department. If you don't get a second letter, I would recommend that you ask the staff member in question to observe your classroom teaching, and discuss that in his/her letter (and not just your interest in pedagogy).

Yes.  You should ask someone who can provide detailed information about the quality of your teaching and who the hiring committee will view as qualified.  I do not see how the letter writer's department is relevant.  Consider that ability to work across disciplines is widely expected.  If the letter writer is a teaching expert that could be beneficial.

Small cautionary note: in some situations, "teaching experts" are considered so exactly and only because they "do research in" teaching, and are in a department or group with a corresponding label. It does not necessarily mean much about the practice of teaching, etc. Comments from a same-content-matter faculty about content-matter-relevant teaching might be better.

A typical case where non-teaching staff can write teaching recommendation letters for someone is when someone from the administration has the role to design and gather teaching evaluations. Such staff member can provide hard quantitative and qualitative evidence of the quality of teaching.
Of course, this kind of letter cannot give actual facts, except by citing what students have written in their evaluations.


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Do postdocs in the United States generally get annual raises?
Do postdocs in the United States get raises in general? (Is this different for postdocs hired under specific grants vs postdocs hired through departments, such as in mathematics?) If there are raises, how are they determined?

Often there are institutional policies that control this, along with the available grant budget.  Everything is ultimately subject to the approval of the funding agency and compliance with government regulations.  If you're writing a proposal to hire a postdoc you should talk about this with your research office.  If you're thinking about accepting a postdoc offer you should ask about pay raises (and fringe benefits!)

You probably also need to specify country and context.

@JeromyAnglim what do you mean by context exactly?

@AruRay I'm not sure what the perfect scope for this question would be to make it useful given that the answer depends on a lot of factors. Country is  the main consideration that jumps out at me. But I imagine other factors would be relevant and what those factors are would probably also vary by country.

You are probably better of talking to the personel department of your university, or maybe your university has a department that helps with external funding and they could help you further on some of the specifics.

@AruRay It really depends on the country, also because different countries might attribute different meanings to the term.

From my experience in the US, it is typical for a postdoc to be on a fixed "short term" contract where there are certainly no "promotion" raises, but might or might not provide cost-of-living increases.
A one-year contract will almost certainly contain no salary increase; for a 2- or 3-year contract, they will be minimal at best.

In my experience (U.S., both East and West coasts) where postdocs are state employees, they will get whatever nominal raise is given across the board to state employees, if such a raise occurs. This is what happened both when I was a postdoc, and it is standard practice for us to build small raises into the budget for postdocs.

I think it would be helpful to supplement this answer with geographic information: e.g. does your experience pertain to US / Canada / Europe / elsewhere [e.g. UK!!]...For instance, I work at the "University of My State."  Postdocs at my university are state employees in the sense that their salaries can be publicly accessed on a "My State's Open Records" webpage.  But in my experience there are zero raises given "across the board to state employees" in My State.  Which does not falsify your answer -- but still, I think you see what I mean.

@PeteL.Clark see edit.

In the UK, postdoctoral Research Fellows, just as permanent academic members, are normally entitled to a annual increase of a salary spinal point, up to a maximum of the salary band. The precise arrangements are of course University-specific.

Please note that the question is tagged "United States"

@jakebeal I was not when I answered it.


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How should I begin my meeting with my former teacher whom I haven't been in contact with for three years?
I am going to meet my former teacher in my former school. We have some interests and hobbies in common, but we had not been in contact for several years.
I want to be careful about etiquette and manner. I don't want her to think me impolite by beginning the conversation with sentences like "Hello Prof. ABC. How was your recent journey in Japan? Had you brought me a souvenir of Tokyo?"
She has agreed to write a few recommendation letters for me to apply for multiple programs at several universities. Should I say "Can we talk about my recommendation letters first because you have agreed to help me..." I am a bit nervous for the meeting with her this Friday.

If she has already agreed to write you a recommendation letter, I would think the most nerve-wracking part is over. At least for me, meeting with professors and not knowing with 100% certainty that they would write a letter for me was the source of most of my anxiety over the meetings.
I would definitely not ask if she brought you a souvenir from Japan (or anywhere else) unless this is a culturally acceptable thing (at least in the US, such a question would likely be considered strange at best and rude at worst). I would also avoid questions/topics that can be considered personal, like her living situation, love life, et cetera.
I think it would be fine to ask her about her travels (e.g., "tell me about Japan"), or ask her about her current research or experience at the school. At least to me, those are innocent questions that also show that you have an interest in what she has been doing. From there, you can lead the conversation to what you have been doing and what you plan on doing in graduate school, and this naturally leads to a discussion of the recommendation letter.


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What is expected in a Thesis Abstract, on a math job application?
I'll be finishing my PhD in May, so I'm applying for jobs. I have my application materials prepared and have been sending them out. Occasionally an application demands something I don't already have prepared, leaving me to decide if it's worth creating that extra item to apply for that job.
As far as I can tell, a thesis abstract is basically like the introductory portion of the research statement, which I already have prepared. If I was asked for a thesis abstract instead of a research statement, I would chop down the latter to create the former.
The problem is, there is a job I'm very interested in that asks for both. I'm not sure how to interpret this. What are they expecting?

The few times I was asked for such a thing, I literally copy-pasted the abstract for my thesis into a document and submitted it.

I was thinking about doing that... Did it work?

mathjobs doesn't want to tell me which jobs asked for it back when I applied so I'm not sure (I got two postdoc offers that round but I'm pretty sure those places didn't ask for a thesis abstract). Noone emailed me to tell me that I'd done it wrong though. Usually there is a contact person listed in each mathjobs ad that you could contact to ask for details, but if say the deadline is tonight I would recommend just copy-pasting thesis abstract, or making up a thesis abstract if your thesis doesn't exist yet.

Cool. I just wrote an email to the contact person given. I have a couple weeks before the deadline actually.

In principle though, the introduction to your research statement and your thesis abstract can be (but isn't always) quite distinct (my thesis was a subset of my research statement). A research statement should have at least something to say about where you envision your research going, but a thesis abstract is mostly limited to the contents of your thesis.

Yes, there is a big difference between the 2 for me as well. My RS intro has a lot of historical context, and ideas about future work. My "thesis abstract" just says what I proved with minimal context.

@AruRay why the tag changes? It's not clear to me why [tag:thesis] and [tag:abstract] are inappropriate, since this question does seem to primarily be about a thesis abstract.

@ff524 the description for the thesis tag says: "Queries related to initiation, preparation, edit and presentation of a research thesis which is a long research report including personal research conclusions and outputs.", and this question does not seem to be about that at all. The description for abstract says: "An abstract is a brief summary of a research article, thesis, review, conference proceeding ...

... to help the reader quickly ascertain the paper's contribution to the field." I could possibly be convinced that this question is about abstracts, but it's more about what is meant when one says abstract in a particular job application portal.
Anyway, to me the question is not about writing an abstract for a thesis, which is why I think the thesis tag in particular, and the abstract tag to a lesser extent, are inappropriate.

@AruRay Can you please turn your comments into an answer so that I can vote for it?

The few times I was asked for such a thing, I literally copy-pasted the abstract for my thesis into a document and submitted it. mathjobs doesn't want to tell me which jobs asked for it back when I applied so I'm not sure (I got two postdoc offers that round but I'm pretty sure those places didn't ask for a thesis abstract). No one emailed me to tell me that I'd done it wrong though. Usually there is a contact person listed in each mathjobs ad that you could contact to ask for details, but if say the deadline is tonight I would recommend just copy-pasting the thesis abstract, or making up a thesis abstract if your thesis doesn't exist yet.
In principle though, the introduction to your research statement and your thesis abstract can be (but isn't always) quite distinct (my thesis was a subset of my research statement). A research statement should have at least something to say about where you envision your research going, but a thesis abstract is mostly limited to the contents of your thesis.