Let $t>0$ and $E$ a Lebesgue measurable set with $\mu(E)=t$. If $s\in(0,t)$, show that it exists $A\subset E$ with $\mu(A)=s$.
I can show the claim if $E$ is contained in a finite closed interval [-a,a] which is in general not the case.
Is it true that $E$ is contained in such an interval almost everywhere, i.e. that $\mu(E\cap [-a,a])=t$ and $\mu(E\setminus [-a,a])=0$? I think then my proof would still work.
Answering the explicit question in your post: no, $E$ is not always contained in such an interval almost everywhere. Consider $$ E = \bigcup_{n = 1}^\infty \left[n, n + \frac{1}{2^n}\right]. $$ Then $E$ is Lebesgue-measurable, and $\mu(E) = \sum_{n = 1}^\infty \frac{1}{2^n} = 1$, but for every finite closed interval $[-a, a]$, there is an $n > a$ with $[n, n + 2^{-n}] \cap [-a, a] = \emptyset$. Consequently, $$ \mu(E \setminus [-a, a]) \geq \mu([n, n + 2^{-n}]) = 2^{-n} > 0. $$
EDIT: I also thought about the result you want to prove and found the following general result: given a measurable set $E$, the map $$ \mu_E: \mathbb{R}^+ \to \mathbb{R}^+: x \mapsto \mu(E \cap [-x, x]) $$ is uniformly continuous. Indeed, let $x < y \in \mathbb{R}^+$. Then, first of all, $|\mu_E(y) - \mu_E(x)| = \mu_E(y) - \mu_E(x)$, by monotonicity of $\mu$. Also, \begin{align*} \mu_E(y) - \mu_E(x) &= \mu(E\cap[-y, y]) - \mu(E \cap [-x, x]) \\ &= \mu( (E \cap [-x, x]) \cup (E \cap ([-y, -x) \cup (x, y]))) - \mu(E \cap [-x, x]) \\ &= \mu(E \cap [-x, x]) + \mu(E \cap ([-y, -x) \cup (x, y])) - \mu(E \cap [-x, x]) \\ &= \mu(E \cap ([-y, -x) \cup (x, y])), \end{align*} where the penultimate equality follows from the fact that $E \cap [-x, x]$ and $E \cap ([-y, -x) \cup (x, y])$ are disjoint sets. Now, as $E \cap ([-y, -x) \cup (x, y]) \subseteq [-y, -x) \cup (x, y]$, we have $$ \mu(E \cap ([-y, -x) \cup (x, y]) \leq \mu([-y, -x) \cup (x, y]) = 2(y - x). $$ Thus, we find that $|\mu_E(y) - \mu_E(x)| \leq 2(y - x)$, and by symmetry, we get $$ |\mu_E(y) - \mu_E(x)| \leq 2 |y - x| $$ for all $x, y \in \mathbb{R}^+$. It follows that $\mu_E$ is uniformly continuous.
How does the desired result follow from this? Note that $\mu_E(0) = 0$ and that $\lim_{x \to +\infty} \mu_E(x) = \mu(E)$. As $\mu_E$ is continuous, it follows from the intermediate value theorem that for each $s \in [0, \mu(E))$, there is an $x \in \mathbb{R}^+$ such that $\mu_E(x) = s$.