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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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. There are no teaching obligations. Postdoctoral Research or more senior research associates are expected to participate actively in the intellectual activities of Princeton University. Applicants must have
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will include making progress on their own research projects, teaching the equivalent of one course each year, and actively participating in the intellectual community of the University Center for Human
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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Theory for a position starting in September 2026. The researcher's duties will include making progress on their own research projects, teaching the equivalent of one course each year, and actively
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will include making progress on their own research projects, teaching the equivalent of one course each year, and actively participating in the intellectual community of the University Center for Human
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of such efforts. Responsibilities will include activities such as working with large public datasets, designing and implementing relevant experiments writing manuscripts, presenting research, and mentoring
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is subject to the University's background check policy. The work location for this position is in-person on campus at Princeton University.Information about the research activities of the Department
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performance. Appointments will be made to the rank of Postdoctoral Research Associate; when teaching, the candidate will hold the secondary part-time rank of Lecturer. Qualifications: The successful candidate
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, lipid vesicles, polymer physics, active materials, single molecule biophysics, biomaterials, materials chemistry, fluid mechanics, rheology, and computational modeling. Candidates should apply at https