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candidates with a background in political science, economics, modern history, sociology, anthropology, law, business, and other disciplines bearing on the study of globalization to apply. The postdoctoral
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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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related field (e.g., statistics, computer science, electrical engineering, applied mathematics, or operations research) before May 2025 are encouraged to apply. Ideal candidates will display outstanding
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, working under the guidance of Dr. Arash Adel, Assistant Professor in the School of Architecture and Associated Faculty of the Department of Computer Science. The desired start date is Spring 2025
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the Department of Chemical and Biological Engineering to study the biochemical and mechanical mechanisms that define pattern formation during branching morphogenesis of the lung and mammary gland. Further
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the guidance of Dr. Arash Adel, Assistant Professor in the School of Architecture and Associated Faculty of the Department of Computer Science. The desired start date is Spring 2025. Appointments are for one
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materials:1.A curriculum vitae; 2.A research proposal (not to exceed 1,500 words) describing the research project(s) the applicant plans to work on during the fellowship. Please provide an indicative title
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, computational fluid dynamics and material science, dynamical systems, numerical analysis, stochastic problems and stochastic analysis, graph theory and applications, mathematical biology, financial mathematics
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: 277839339 Position: Postdoctoral Research Associate Description: The Ferris Research Group in the Mechanical and Aerospace Engineering Department at Princeton University invites applications for a
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are of relevance. Outstanding scholars anywhere in the world are eligible to apply. NCGG invites candidates with a background in political science, economics, modern history, sociology, anthropology, law, business