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#:39540 Job Summary: How can we turn the vast and rapidly growing collections of publicly available biological data into reusable engines for discovery? And how do we build the software infrastructure
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experience using statistical software (e.g., R and Python) and AI tools (e.g., Claude Code) are a key requirement for the position. Successful candidates should show potential to excel in tasks related to meta
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on-site presence as needed, in accordance with UVA’s remote work guidelines. For information on resources for postdocs at UVA, visit https://postdoc.virginia.edu/ . To learn more about UVA and in
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of Postdoctoral Affairs, and campus groups. Job Description Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective
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of Bayesian estimation theory, stochastic processes, and statistical inference. Proficiency in scientific programming (Python, MATLAB, C++) and software engineering best practices (Git, testing, documentation
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: Civil and Environmental Engineering Chemical Engineering Postdoc Appointment Term: 1 year with possibility of extension Appointment Start Date: The position is available immediately and the start date can
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join the group to develop AI and machine learning based software to assist clinical workflow and pre-clinical studies. Required Qualifications: Ph.D. in a physical science or engineering field Strong
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for unseen regimes, including rare events. The postdoc will be expected to lead independent research directions while collaborating with a team comprising domain scientists, experts in climate physics and
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Zanna, the successful candidate will focus on developing generative machine learning models for complex dynamical systems for probabilistic forecasts. The postdoc will be expected to lead independent
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Stanford Departments and Centers: Woods Institute Postdoc Appointment Term: One-year appointment, full-time (100% FTE), with the possibility of renewal for a second year, contingent upon performance and