Stochastic thermodynamics studies energy exchanges at the scale of k_B T (where k_B is the Boltzmann constant and T the temperature). Our experiments enable unprecedentedly precise measurements in this field using a model system with two degrees of freedom: position and velocity. The research directions are highly promising: we can bring thought experiments such as a Maxwell’s demon to life to harness thermal fluctuations; explore the minimal energy required to process information in logical operations; and study engine cycles (such as the Carnot cycle) using a single-particle gas. Numerous open questions about the relationship between information and energy exchange drive our experimental approach and lead to collaborations with international experts in the field, involving theoretical investigations, AI-based optimization, exploration of quantum fluctuations, and connections to biophysics. Our experiments offer a wide range of opportunities for a PhD candidate to express creativity, from highly experimental work (micro-mechanical optimization, real-time feedback control) to fundamental studies (advanced analytical modeling), as well as signal processing (real-time implementation of protocols via artificial neural networks). A solid foundation in statistical physics and strong scientific curiosity are the only prerequisites!