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plasma physics. The successful candidate will investigate key processes related to magnetosphere–ionosphere coupling, energetic particle dynamics, and the structure and dynamics of magnetic fields and
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group in the Department of Physics & Astronomy at the University of Iowa invites applications for a postdoctoral research position. The successful candidate will work on the development of axion–plasma
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plasma metabolomic signature of almond intake using samples from a dose-response randomized controlled feeding trial. The Postdoctoral Associate will contribute to all aspects of the research, including
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other immune parameters in plasma and other sample types. • Perform in vitro viral phenotyping assays • Maintain multiple copies and records of all data collected • Assist in the organization and curation
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | 3 months ago
critical constraints on physical models of SEEs. This opportunity has a particular focus on data from the Hinode EUV Imaging Spectrometer: identifying key datasets from the 18-year mission; performing plasma
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upgrades of ALPHA. Candidates should have a PhD in experimental particle physics or the equivalent, and preference will be given to candidates having experience with cryogenics, microwave electronics, and
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preparation (20%) -mentoring PhD and MSME students (10%) -laboratory organization and management (10%) -other duties as assigned (5%) *In this position you will be expected to perform high level experimental
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Plasma Physics Lab and in the Physics, Geosciences, and Mechanical and Aerospace Engineering Departments, and at the nearby Institute for Advanced Study. The expected start date is September 1, 2026
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funding. Appointment Start Date: Fall 2025 Group or Departmental Website: https://hph.stanford.edu/careers (link is external) How to Submit Application Materials: Submit all application materials
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://postdoc.wustl.edu/prospective-postdocs-2/ . Lab website: https://cruchagalab.wustl.edu/ . Research Projects: Plasma, CSF and Brain Proteomic analysis. Biomarker identification through the use of machine learning