56 computational-physics-superconductor Postdoctoral research jobs at Pennsylvania State University
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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. JOB DESCRIPTION AND POSITION REQUIREMENTS: The Eberly College of Science, Department of Physics at The Pennsylvania State University is seeking to fill one postdoctoral scholar position in computational
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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the opportunity to work with faculty and students from physics, mathematics, and/or computer science. We are particularly interested in candidates with expertise in open quantum systems and at least one
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physics research under my supervision on topics including quantum many-body physics and quantum statistical mechanics. The research is expected to be partly analytical and partly computational in nature
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. JOB DESCRIPTION AND POSITION REQUIREMENTS: The Department of Physics at Penn State is seeking to hire a Postdoctoral Scholar. This individual will work with Dr. Reka Albert on performing computational
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of physics beyond the Standard Model, using analytical and computational approaches. The successful applicant will join Dr. Carlos Blanco's research group with significant academic freedom to pursue
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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Scientific Machine Learning. The successful candidate will develop and deploy state-of-the-art SciML algorithms in high-performance computational physics codes. We accept applications from all candidates with
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available codes and existing high performance computing (HPC) infrastructure Identify key physics of the systems through simulations to drive actionable design recommendations Identify gaps between existing