linear algebra - Matrices whose nullspace is nicely shaped

I'm looking for natural conditions on $a_{ij}$ to guarantee that the null space of the $ntimes m$ matrix $A=(a_{ij})$ has a nice basis.

The null space of { {1,-2,1,0,0}, {0,1,-2,1,0}, {0,0,1,-2,1} } is the set vectors $langle x_1,x_2,x_3,x_4,x_5rangle^T$ with $x_1,dots,x_5$ in arithmetic progression or constant, i.e., there is a degree zero or one polynomial $p(t)$ with $x_i = p(i)$. The null space of { {3,3,-23,21,-4}, {6,3,-38,36,-7} } consists of points for which there is an at-most-quadratic $p(t)$ with $x_1=p(1),x_2=p(2),x_3=p(3),x_4=p(4),x_5=p(6)$, with that last 6 not being a typo.

In particular, I need a basis for the null space of the form ${langle 1,1,dots,1rangle^T,langle x_1,dots,x_mrangle^T, dots, langle x_1^{m-n-1},dots,x_m^{m-n-1}rangle^T}$, with the $x_i$ distinct (not necessarily integers).

As another specific example, consider the matrix { {3,-3,1,0,-1}, {20,-16,5,-9,0} }. I happen to know that the null space of this matrix has basis $langle 1,1,1,1,1rangle^T, langle 1,4,7,-1,-2 rangle^T, langle 1^2,4^2,7^2 ,(-1)^2,(-2)^2rangle^T$, but only because I made the matrix that way. Even with a specific matrix such as this, I don't know how to compute such a basis, or to guarantee that one exists or doesn't exist.

Here are the obvious necessary conditions: the rows must be independent; each row must add up to 0; no row can have exactly two nonzero components.

As a specific problem (I've no interest in this as a particular problem, mind you, but it may help the discussion) consider the matrix { {35,-3,-42,10,0}, {15,3,-8,0,-10} }. Does it have such a basis?

For background, I'm looking at constructions of sets $X$ of integers that contain no solutions to a system of linear equations. Such a basis as above means that a solution has x_i in the image of a polynomial, and I already know how to construct sets that don't have those (arithmetic progressions are a special case).