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optimization of waste heat harvesting. Your role will be to simulate the heat transfer processes between façade panels and thermoelectric generators, focusing on maximizing waste energy recovery efficiency. You
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, dynamic building simulations, experiments in climate chambers and field studies to evaluate the performance of developed control strategies. You will be involved in ongoing national and international
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and reduction of very large data sets, data analysis, and simulations of X-ray scattering and spectroscopy signatures of dynamic processes in battery materials. The theoretical/ simulation efforts
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create multi-fidelity predictive models that integrate data from quantum simulations and experiments, using techniques such as equivariant graph neural networks with tensor embeddings. We aim to train
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the experiments. You will also have the opportunity to carry out your own simulations with our numerical model. Qualified applicants must have: A strong drive to move the frontiers of science. Ample experience with
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and MSc students. In the project you should: Design and implement enzyme libraries using generative AI tools such as RFdiffusion2 or BoltzDesign. Perform molecular dynamics simulations to assess enzyme
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optimization, for enhancing light trapping in nanostructured thin-film solar cells. Your role will focus on developing and applying large-scale electromagnetic simulations to identify optimal nanostructured
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molecular dynamics simulations and in silico screening to assess inhibitor-target interactions and predict selectivity. Clone, express, and purify top candidates using high-throughput bacterial systems and