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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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Group Leader and Professor AI in Biology - Dept of Computer Science and Dept. Electrical Engineering
but are not limited to: development of new AI architectures for biology and hybrid models that combine deep learning with mechanistic models; foundation models of genome regulation using single-cell and
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learning with mechanistic models; foundation models of genome regulation using single-cell and spatial multi-omics data; AI-based modeling of protein structure and protein interaction networks; AI-based
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biennial CMB retreat; Support and report on initiatives from our internal communities, including the Postdoc committee, PhD committee, Tech committee, and Eco teams; Maintain the Centers’ relationships with
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degree and a minimum of 2-3 years of work experience; a background in life sciences is considered an asset. Eagerness to learn, develop and contribute to the growth and visibility of the Center