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algorithmic and theoretical foundations of reinforcement learning applied to complex, high-dimensional dynamical systems. The project focuses on the intersection of deep reinforcement learning
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Laboratory, which investigates how post-translational modification (PTM) networks regulate protein function, genome stability, and cellular decision-making. The laboratory builds on internationally
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contribute to new strategies for controlling protein function in complex biological environments. The research project: PROTÆCT This postdoc position is part of the Villum Foundation funded project
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reference datasets for compositionally complex, defect-containing and structurally disordered crystalline materials. Develop, train, validate and benchmark machine-learned interatomic force fields for
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Postdoc in first-principles modelling and machine-learned force fields for correlated disorder in...
working on battery electrodes, thermoelectric materials and ferroelectric relaxors. Main tasks Generate and curate ab initio reference datasets for compositionally complex, defect-containing and
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Group Leader/Associate Professor in live-cell in vitro analysis of cellular function and dysfunct...
internationally in academic networks and to public audiences Teaching and supervision of Bachelor’s and Master's degree students and contributing to the development of new teaching activities Contributing