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candidate will join the Nelissen lab , and will work alongside scientists to develop and implement a mobile 3D machine vision system for small plants. The ideal candidate will have a background in
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perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and
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in vivo perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and
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groups explore how the brain and nervous system develops, ages and functions in health and disease, in particular neurodegenerative and neurodevelopmental conditions, by bridging disciplines, from
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models of immune diseases and causal learning to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of experimental immunology
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-scale in vivo perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and
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-scale in vivo perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and
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perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and experimental
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perturbation experiments to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of advanced machine learning and experimental
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mouse models of immune diseases and causal learning to uncover how genes shape immune-cell states and predict how the immune system responds to interventions. This tight integration of experimental