216 formal-verification-computer-science Postdoctoral positions at Princeton University
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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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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 computer science, sociology to psychology, engineering to environmental studies - to make novel insights and to tackle the full complexity of human health.We seek applicants to join any of the several
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, computer science, electrical engineering, applied mathematics, or operations research) before May 2025 are encouraged to apply. Ideal candidates will display outstanding ability for research and a record of
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focus on innovation, entrepreneurship, and technology and society, is developing an emerging research and teaching program in design that embraces Princeton's commitment to the betterment of humanity
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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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: 278599133 Position: Postdoctoral Research Associate Description: The Department of Ecology and Evolutionary Biology (EEB) at Princeton University invites applications from postdoctoral research associates
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, molecular biology, biochemistry, physics, computer science, and genetics. The term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending
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throughout the university, including physics, electrical engineering, computer science, chemistry, and mechanical engineering. Research areas include foundational quantum science, quantum materials, devices
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biology-experimental and/or theoretical biophysics-experimental and/or computational genomics-computer science, statistics, and/or machine learning with applications relevant to genomics-bioinformatics