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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
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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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(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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the laboratory is not required. We are especially interested in individuals who are intellectually curious, enjoy learning new approaches, and want to pursue mechanistic questions across conventional disciplinary
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for additional information about the Department of Medicine. About the Campus: To learn more about the Indiana University-Indianapolis campus, please visit: https://indianapolis.iu.edu/about/ About Indianapolis
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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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efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all
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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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Surgery Campus IU School of Medicine Indianapolis Position Summary POST-DOCTORAL POSITION IN STEM BIOLOGY in the Department of Otolaryngology-HNS We are looking for a motivated and creative post-doctoral
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handling and the potential participation in neurobehavioral testing. Work may also involve electrode implantation surgery and EEG recording in rodents (initially semi-independently under the PI’s supervision