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at molecular, cellular, and organismal levels. We have uncovered key roles for RNA modifications and translational control in regulating normal and malignant stem cell function (Guzzi et al., Cell 2018; Cieśla
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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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experimentation. A solid molecular biological toolkit is a plus. The postdoc period is 2 years from December 1st, 2025 with a possibility of extension. We recommend that as an international applicant, you take the
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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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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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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 are supported by
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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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bioinformatic analysis of NGS data. Hands-on experience in generating high-quality ChIP-seq data. Hands-on experience in culturing mammalian cells. Experience in molecular biology techniques, including use
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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