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are looking for a highly motivated and dynamic PhD student for a position in the Translational Neuroscience team headed by Prof. Rejko KRÜGER. The Translational Neuroscience team's focus lies in
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dynamics and biomolecular condensates contribute to PD co-pathologies in human midbrain assembloid models. The work combines advanced imaging, molecular biology, and functional disease modeling. Key
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unique training environment to advance microbiome science through metaproteomics. The program addresses One Health challenges by integrating research on microbial mechanisms, microbiome dynamics in various
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datasets across broad chemical space Evaluate models through molecular dynamics, simulations, and benchmarks Active Learning in Configurational and Chemical Spaces Integrate uncertainty-aware MLFFs
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, medicine, nursing and midwifery. Research at the department integrates basic and translational, molecular and computational approaches with a focus on cancer biology, as well as clinical research projects in
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background in computational and/or mechanistic modelling of physical, chemical, or biological systems (e.g., PBPK, molecular dynamics) Experience with cheminformatics libraries and chemical datasets is an
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approach. Fundamental research focuses on induced pluripotent stem cell (iPSC)-derived neuronal models to elucidate the molecular and cellular alterations contributing to neurodegeneration in familial and
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular
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apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular dynamics (MD) simulations