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and diseases Relevant experience with animal models and laboratory skills related to molecular biology Language skills and interpersonal skills Place of employment The place of employment is at
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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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. 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-substrate
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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
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experienced in working with in vivo animal models, preferably models related to perinatology You have strong laboratory-based skills related to molecular biology, neuroscience, immunology You have experience
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tools such as RFdiffusion2 or BoltzDesign. Perform molecular dynamics simulations and in silico screening to assess inhibitor-target interactions and predict selectivity. Clone, express, and purify top
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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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injection, ion transfer, and structural dynamics in realistic and model systems for battery materials. The position will span experimental efforts at large scale X-ray facilities, handling and reduction
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focus on charge injection, ion transfer, and structural dynamics in realistic and model systems for battery materials. The position will span experimental efforts at large scale X-ray facilities, handling
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project supported by the Challenge Programme of the Novo Nordisk Foundation: “Mathematical Modelling for Microbial Community Induced Metabolic Diseases”, led by Prof. Daniel Merkle. The expected starting