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)—topics including, but not limited to: · Physics-informed neural networks (PINN) & neural operators · Physics-aware convolutional neural networks (PARC) · Meta-learning/transfer
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of national research infrastructures. The ideal candidates will have a PhD in a discipline closely related to computational social science by date of appointment (e.g. network science, computer science, data
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to PhD students and other early-career-scholars on the research team. Support the team with data cleaning, project management, and grant submission tasks as needed. Other tasks include various writing and
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will have a PhD with experience in relevant areas of biology, first-author publication(s), and the ability to work well in a highly interactive, creative, and collaborative environment. Postdoctoral
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from the NIDDK and focuses on investigating the role that T1D risk variants play in islet autoimmunity through advanced single-cell techniques. The lab seeks an independent, highly motivated PhD-level
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, other duties may be assigned. Minimum Requirements Qualified candidates must have a PhD in Immunology, Microbiology, Neuroscience, or a related field by the appointment start date. For additional
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of renewal contingent upon satisfactory performance and the availability of funding. Minimum Qualifications: Education: PhD, MD, or equivalent degree is required at the start date. Experience: The ideal
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contact Hong Zhu, Professor, at hzhu2m@virginia.edu. Minimum Requirements: Doctoral degree Preferred Qualifications: PhD in biostatistics, statistics, or a related quantitative field by the appointment
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their communications Data Collection and Analysis: Collect data on the implementation process, including facilitator performance and participant feedback Analyze fidelity data to identify areas where
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ability to learn new software quickly and introduce new useful applications and platforms to the team. Proficient in advanced statistical modeling software (e.g., R, Stata, Matlab) Physical Demands This is