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of their biological counterparts. This project aims to overcome these limitations through a synergistic circuit–device co-design that jointly optimizes both circuit architectures and component properties, ensuring
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the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise from machine learning, optimization, control theory, and applied mathematics
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thermodynamics, energy technology, or systems modelling. Solid knowledge in mathematics, physics, thermodynamics, energy technology, optimization, and programming for system modelling, with experience in tools
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system modelling. Solid knowledge in mathematics, physics, thermodynamics, energy technology, optimization, and programming for system modelling, with experience in tools such as Matlab, or Python