164 scholarship-phd-agent-based-modelling Postdoctoral positions at Princeton University
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biology, cancer biology, chemical biology, biochemistry, cancer genomics, genetics, mass spectrometry, physical chemistry, computational and systems analysis. The term of appointment is based on rank
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postdoctoral and PhD researchers on the team*Interest in developing and applying Large Language Models (LLM) and spatial Machine Learning (ML) modelsSalary and full employee benefits are offered in accordance
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spectrometry-based metabolomics data, in part based on generative AI models of chemical structures. The position is available starting July 2025, and will remain open until excellent fits are found.The
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emerging technologies such as artificial intelligence, quantum technologies, and space-based systems, including large satellite constellations. A recent PhD in physics, engineering, computer
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experience in scholarly research and a strong commitment to excellence in education are encouraged to apply. PhD is required. Applicants must apply online at https://www.princeton.edu/acad-positions/position
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experience in scholarly research and a strong commitment to excellence in education are encouraged to apply. A PhD in Materials Science, Optics, Physics, Chemistry, Electrical, Chemical, Mechanical, Civil
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or more senior research positions to analyze and model the delivery of clean energy and industrial decarbonization infrastructure associated with net-zero transitions. The role will report to the Andlinger
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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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to ion beams with well-controlled energies and incident angles for benchmarking and validation of theoretical calculations and computational physics and chemistry modeling of important surface processes
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. 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; those hired at more