40 computational-physics-"https:"-"https:"-"https:" Postdoctoral positions at Yale University
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molecular data using advanced computational and statistical approaches to identify early biomarkers of neurodegeneration. Qualifications: PhD in Biomedical Engineering, Neuroscience, Neuroimaging, Physics
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and kinetic modeling. A PhD in biomedical engineering, physics, or a related field is required. However, interested candidates with a strong computational background and interest in getting involved in
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Eastern Time Description The Yale Center for Natural Carbon Capture (YCNCC) is accepting applications for its Postdoctoral Fellowship Program . The YCNCC was established in 2021 to advance fundamental and
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. The ideal candidate will have completed medical school and have a strong background in science, with university studies in biology, chemistry, physics, computer science, or similar fields, and an interest in
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, Full-time (renewable) Position Description The research group of Dr. Xuehong Zhang at Yale University is seeking a highly motivated Postdoctoral Associate to join a multidisciplinary research program
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pain under the mentorship of Dr. Nitya Bakshi, Associate Professor of Pediatrics and Director of the Pediatric SCD Program at Yale University. The research laboratory is focused on the study of chronic
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, physics, or other quantitative disciplines), or expected within 6 months. Demonstrated experience in in vivo two-photon imaging using calcium indicators in mice. Strong quantitative and analytical skills
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software or computation time). Important Dates and How to Apply The application deadline is on October 1, 2026. Please note that our review process may take several weeks. Applicants will be contacted
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), through its Democratic Innovations program. However, it is physically headquartered at the University of South Carolina, under the direction of Prof. Bagg. The holder of the postdoctoral position will thus
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program, our laboratory addresses three central questions: ● Why do breast cancer therapies stop working? ● How can the patients developing resistance, and the biology driving it, be identified from a