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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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at CCB. This includes agentic workflows that help researchers find suitable methods, write and run analysis code, and work with multi‑omics and spatial data. You will critically evaluate these tools, bring
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related field. Demonstrated expertise in multi-omics integration and large-scale data analysis. Strong programming skills (e.g., R, Python, workflow systems). Proven publication record in peer-reviewed
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understandYou appreciate multi-disciplinarity for problem-solvingYou can work well in a team and independentlyYou bring precision and critical reflection to your workYou have a strong ability to multi-task and
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understand You appreciate multi-disciplinarity for problem-solving You can work well in a team and independently You bring precision and critical reflection to your work You have a strong ability to multi-task
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About the lab The Laboratory of Causal Systems Immunology combines causal inference, probabilistic AI and large-scale in vivo perturbation experiments to uncover how genes shape immune-cell states
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About the lab The Laboratory of Causal Systems Immunology combines causal inference, probabilistic AI and large-scale in vivo perturbation experiments to uncover how genes shape immune-cell states
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team and independently You have a strong ability to multi-task and meet deadlines You enjoy other cultures and are respectful of others and their different ideas/opinions We offer Opportunity
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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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from large‑scale immune repertoire data and in translating these insights into rational, model‑driven prioritization of high‑quality nanobody candidates. Working at the interface of immunology, protein