Stronger notions of uniformizations? One gap that I was always aware that I don't really understand is between non uniform and uniform computational complexity where the circuit complexity represents the non uniform version and Turing machines is were things are uniform. I suppose "uniform" is a way to restrain the class of algorithms, e.g. not allowing an entirely different circuit for a problem with n variables compared to a problem of n+1 variables. 

My questions are: 1) It there a description of uniformity just in terms of circuits, and 2) Is it possible to come with an even stronger form of uniformity and thus to give even more restricted notion of what effective (or restrained) algorithms in P are? 

Late clarification: my intention in question 2 is about a restricted class of algorithms that "practically" has the same power as the class of polynomial algorithms.
I think the answer to you first question is negative: A circuit has a fixed number of inputs, and thus, IMO, we can only talk about "families" of circuits, rather than just one uniform circuit.

Regarding your second question, you may note that there are "uniform families of circuits," whose description is generated by a Turing machine. That is, let $\{C_n\}$ be a uniform family of circuit, and let $M$ be a Turing machine. Then, for each $n$, $[C_n] = M(1^n)$, where $[C_n]$ denotes the description of $C_n$.

There are several complexity classes below P, defined by uniform families of circuits. For example:

$\mathbf{NC}^i$ is the class of decision problems decidable by uniform boolean circuits with a polynomial number of gates and depth $O(\log^i n)$.