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and patient-reported outcomes; (b) observational research and comparative effectiveness studies; (c) intervention studies; (d) clinical informatics, mobile/electronic health; (e) machine learning
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and early-onset cases without a known genetic cause. We are also interested in genetic interactions (epistasis), tandem repeats, machine learning, and other areas of AD research that have not yet been
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the resulting data from the experiments. Required Qualifications: Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including
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, molecular profiling, and transgenesis, and is passionate about learning systems neuroscience and all-optical physiological approaches to the study of brain-body interactions. Our mentorship goal
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with researchers both at Stanford and the U.S. Census Bureau. The position is open to recent graduates of PhD programs in economics, statistics, sociology or related data science fields, preferably with
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Obradović is seeking a postdoctoral scholar to join her research group in the Graduate School of Education at Stanford University. We encourage applications from individuals from a broad diversity of PhD
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: Candidate must have a strong quantitative background, with a PhD in computational biology, bioinformatics or related field including bioengineering, computer science, statistics, or mathematics. Strong
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subsea digital twin of deep-water mooring lines for floating offshore wind turbines. The digital twin will be integrated with machine learning algorithms for detection of primary entanglement due
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maintaining protocols for analyses and quality control Pursuing independent research projects related to lead contamination and/or environmental health topics (up to 10% time). Required Qualifications: PhD in a
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lab in Stanford’s Psychiatry Department, led by Neir Eshel, MD, PhD. We are looking to hire curious and ambitious postdocs to join our team. Lab projects focus on the neural circuitry of reward-seeking