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an advantage: Deep learning or machine learning Structural bioinformatics Protein structure prediction and modelling Molecular simulations Membrane proteins or membrane biophysics Scientific software development
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an advantage: Deep learning or machine learning Structural bioinformatics Protein structure prediction and modelling Molecular simulations Membrane proteins or membrane biophysics Scientific software development
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who show genotypes and biomarker phenotypes relevant to Alzheimer’s disease. Key responsibilities: Coordinate the derivation, quality control and biobanking of participant-derived iPSC lines, in
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who show genotypes and biomarker phenotypes relevant to Alzheimer’s disease. Key responsibilities: Coordinate the derivation, quality control and biobanking of participant-derived iPSC lines, in
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and predict how the immune system responds to interventions. This tight integration of advanced machine learning and experimental immunology allows us to tackle fundamental biological questions with
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and predict how the immune system responds to interventions. This tight integration of advanced machine learning and experimental immunology allows us to tackle fundamental biological questions with
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About us The Laboratory of Causal Systems Immunology combines large-scale in vivo perturbation experiments, advanced mouse models of immune diseases and causal learning to uncover how genes shape
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About the lab The Laboratory of Causal Systems Immunology combines large-scale in vivo perturbation experiments, advanced mouse models of immune diseases and causal learning to uncover how genes
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, ensemble modeling strategies. Run large‑scale structural predictions and interface scoring on HPC infrastructure. Rank nanobody candidates using structure‑based affinity and interface
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, ensemble modeling strategies. Run large‑scale structural predictions and interface scoring on HPC infrastructure. Rank nanobody candidates using structure‑based affinity and interface