164 scholarship-phd-agent-based-modelling Postdoctoral positions at Princeton University
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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
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of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may
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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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position. Applicants should have a PhD degree (or expect to receive a PhD degree by June 15, 2025) in Psychology or allied fields (e.g., Sociology) with an interest in conducting research relevant to racial
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collaborate with members of these different research groups. Individuals with evidence of experience in scholarly research and a strong commitment to excellence in education are encouraged to apply. PhD in
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-disciplinary environment. The Term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory performance and continued funding
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positions to work in experimental condensed matter physics with focus on angle-resolved photoemission (ARPES) and scanning tunneling spectroscopy (STS/STM) based studies of topological, strongly correlated
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leading and mentoring graduate and undergraduate students. A PhD in relevant fields of energy storage, electrochemistry, and materials characterization is required. Experience with solid electrolytes
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the scholarly and academic activities of the program. The term of appointment is based on rank. Positions at the postdoctoral rank are for a 12-month term during the 2026-2027 academic year with the possibility
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, to study novel renewable energy technologies. The candidates are expected to have a PhD degree in Chemical Engineering or related field, and have experience with optimization (theory, modeling, and tools