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-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 infer
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knowledge-grounded reasoning with flexible machine learning Tools that reduce manual burden while preserving traceability and clinical interpretability This position offers the opportunity to publish novel
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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 approaches
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welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We
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Experience in one or more of the following areas is preferred: Statistical genetics Human genetics Population genetics Evolutionary genetics Bayesian statistics Machine learning Large-scale genomic data
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities
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knowledge-grounded reasoning with flexible machine learning Tools that reduce manual burden while preserving traceability and clinical interpretability This position offers the opportunity to publish novel
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(kidney biopsy, serum, urine) for comprehensive biomarker profiling. Utilization of machine learning and image processing for advanced tissue analysis. The Herman B Wells Center for Pediatric Research
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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 spatial population
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or interest in the use of artificial intelligence, machine learning, or computational tools in behavioral and experimental economics is appreciated. Strong emphasis will be placed on demonstrated research