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analyzing hyperspectral data and developing machine learning models - Genetic or molecular lab experience - Bioinformatics, or statistical genetics experience - Excellent written and oral communication skills
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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with leading machine learning frameworks and modern AI environments, including multi-GPU model training and large-scale inference on dozens to hundreds GPUs, are required. Additional Qualifications
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to have a strong background in the foundations of machine learning. Special Instructions Required application documents include a cover letter, CV, a statement of research interests, and up to three
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. transformer models). One focus of this work will be on B-cell receptor evolution. Experience in applications of modern machine learning methods as well as in biological data analysis are needed for the position
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novel findings that inform disease etiology. The candidate should be interested in focusing on multi-omic integration analytics, machine learning, and/or AI. In addition to carrying out research
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position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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Fellow to develop and evaluate artificial intelligence methods for physical medical procedures. The fellow will design and implement machine learning models to analyze procedural data, support clinical
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projects, as well as in multiagent systems, including computational game theory, security games, machine learning in multiagent settings, automated planning under uncertainty, social networks and others
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Details Title Postdoctoral Fellow – PKPD Modelling, Lung-on-Chip School Wyss Institute for Biologically Inspired Engineering Department/Area Position Description About the Wyss: The Wyss Institute’s