144 parallel-and-distributed-computing-phd Postdoctoral research jobs at Princeton University
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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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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 have multi-year appointments. A PhD is required
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research levels in the areas of neuroscience, psychology, molecular biology, biochemistry, physics, computer science, and genetics. The term of appointment is based on rank. Positions at the postdoctoral
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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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maps of the distributions of small molecules within the cell. Determining the spatial distribution of small molecules within cells is crucial for understanding fundamental biological mechanisms, but it
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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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. Our lab works in the areas of ultrafast science, nanoscale thermal transport, and microelectronics, for applications in energy-efficient computing, thermal management, and energy conversion. We seek
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. The University also offers a comprehensive benefit program to eligible employees. Please see this link for more information. Requisition No: D-26-MOL-00002 PI277839324 Create a Job Match for Similar Jobs About
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of squamate reptiles; the largest group of terrestrial vertebrates on Earth today with 11,000 species. A Ph.D. in Evolutionary Biology, Computational Biology, or related fields, is required. The work will focus
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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