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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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application to lineage tracing Algorithms for characterizing structural alterations in bulk and single cell whole-genome data Mutational signature analysis for cancer/brain samples Analysis of repetitive
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research team. Key research areas include: Development of low-carbon materials and tunable thermal energy storage materials integrated with smart sensors and advanced algorithms Creation of Digital Twins
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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of complex systems, networks, and large-scale data Machine learning, generative AI, NLP, or algorithmic decision systems Ideal applicants will have a strong background in operations research, statistics
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, generative AI, NLP, or algorithmic decision systems Ideal applicants will have a strong background in operations research, statistics, or computer sciences and the ability to work across disciplinary
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learning algorithms. We combine statistical methods with online reinforcement learning algorithms to develop reinforcement learning algorithms and inferential tools. The successful applicant will be expected
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the areas of immunology, microbiome, and diet. Basic Qualifications Candidates should hold a PhD in the relevant areas or be nearing their PhD defense date. Additional Qualifications The position requires
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Required documents: CV Research summary of PhD work. Cover letter describing your interest in the lab and initial ideas for new research directions or projects you could undertake in the lab. Names and
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lymphoid and non-lymphoid tissues using intravital microscopy techniques. We welcome applications from recent PhD graduates who are interested in this or a related field, particularly those who may bring a