This internship/PhD proposal explores quantum sensing through optimal control of Bose–Einstein condensates (BECs) to maximize the information extracted from a single measurement within finite time. Combining quantum control theory and Fisher information–based estimation, it aims to design and experimentally demonstrate control protocols that reach the quantum precision limit. Experiments will use optical lattices with tunable depth and geometry, enabling precise manipulation of BECs. The first goal is to measure an unknown vector force in 2D while ensuring robustness against quasimomentum dispersion and experimental noise. This work will also pave the way for rotation sensing and interaction-strength measurements. On the theoretical side, control fields will be optimized using GRAPE/Krotov algorithms and reinforcement learning, under realistic hardware constraints. The internship offers a strong dual experience in numerical quantum control and cold-atom experiments within a cutting-edge research environment.