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architectures that combine knowledge-grounded reasoning with flexible machine learning Tools that reduce manual burden while preserving traceability and clinical interpretability This position offers the
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post-doctoral research position under the supervision of Dr. Chris Smith Home | Chris Smith . Our lab studies spatial population genetics, using simulation-based inference and machine learning to
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applications for a post-doctoral research position under the supervision of Dr. Chris Smith Home | Chris Smith . The lab— in the Evolution, Ecology, and Behavior section—investigates machine learning
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for a post-doctoral research position under the supervision of Dr. Chris Smith Home | Chris Smith . The lab— in the Evolution, Ecology, and Behavior section—investigates machine learning approaches for
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Economics to lead research in areas such as Behavioral and Experimental Economics and Applied Microeconomics. Experience or interest in the use or development of artificial intelligence, machine
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to lead research in areas such as machine learning, agentic AI, edge AI, physical AI and AI safety. We encourage applications from scholars who apply interdisciplinary perspectives and share
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) Statistical genetics and polygenic scores Single-cell RNA -seq, proteomics, or other multi-omics analyses Artificial intelligence and machine learning Biobank and electronic health record ( EHR ) analyses
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genetics Human genetics Population genetics Evolutionary genetics Bayesian statistics Machine learning Large-scale genomic data analysis High-performance computing Experience in human population genetics
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or more areas of digital art, including, but not limited to, creative coding; computational, algorithmic and generative art; artifi cial intelligence and machine learning; human-computer interaction
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interdisciplinary perspectives across a variety of domains and complement existing strengths within these departments in bioinformatics, artificial intelligence and machine learning, and expand cutting