225 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions at Princeton University
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estimate for a full-time position; salaries for part-time positions are pro-rated accordingly. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more
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Modern Greek Studies, Byzantine Studies, or Late Antique Studies, including their relation to the Classical tradition. This postdoctoral research fellowship program aims to advance the scholarship
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this position is in-person on campus at Princeton University. For more information about the Niehaus Center for Globalization and Governance fellowship program, please contact Jennifer Bolton, Assistant Director
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for part-time positions are pro-rated accordingly. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information. Requisition No: D-26-PHY-00005
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for part-time positions are pro-rated accordingly. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information.
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at Princeton University.We welcome applications from all areas in mechanical and aerospace engineering, including but not limited to the fields of: Bioengineering Combustion and Energy Science Computational
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join a vibrant intellectual community dedicated to advancing research on blockchain, decentralized technologies, and their applications, across computer science, economics, law, political science
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for peer reviewed publications Qualifications*Ph.D. in Environmental/Civil Engineering, Computer Science/Engineering, Data Science, or a closely related field*Proficiency in Python or other tools and ML
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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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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