153 high-performance-quantum-computing Postdoctoral positions at Princeton University
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, lipid vesicles, polymer physics, active materials, single molecule biophysics, biomaterials, materials chemistry, fluid mechanics, rheology, and computational modeling. Candidates should apply at https
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. Applicants with experience in the following areas are encouraged to apply: Experimental condensed matter physics, cosmology and astrophysics, particle astrophysics and dark matter, high energy, atomic, pulsar
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: 270175792 Position: Postdoctoral Research Associate Description: The High Meadows Environmental Institute (HMEI), (https://environment.princeton.edu/) invites applications for postdoctoral research associates
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satisfactory performance. 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
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The Department of Electrical and Computer Engineering has opening for postdoctoral research positions in the following fields: 1. Microfluidic and Lab-on-Chip development in a multidisciplinary lab
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catalysis, and/or plasma-assisted catalysis is of significant value to participate in other ongoing projects in the lab. Experience with the design, construction, and operation of high-vacuum instruments and
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incident angles for benchmarking and validation of theoretical calculations and computational physics and chemistry modeling of important surface processes occurring at plasma-material interfaces in fusion
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learning/computer science. 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
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one year, with the possibility of renewal pending satisfactory performance and continued funding. Interested applicants must apply online at https://puwebp.princeton.edu/AcadHire/position/39021 and
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, combines advanced system neuroscience and computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models