57 physics-"https:"-"https:"-"https:"-"https:"-"https:"-"Caltech" positions at Argonne
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The High Energy Physics (HEP) Division, in collaboration with the Materials Science Division (MSD) and Q-NEXT at Argonne National Laboratory, seeks a postdoctoral researcher to focus on applied
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processing approaches and dry head-end separations methods; evaluating process performance; and contributing to technical reports, publications, and sponsor deliverables. The successful candidate will work
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nanoscience and nanotechnology. We seek a highly motivated scientist to help advance CNM’s research leadership in microelectronics, with particular emphasis on device physics, transport measurements, and
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The Chemical and Fuel Cycle Technologies Division is seeking a Postdoctoral Appointee to conduct research in chemical process engineering, separations, and process intensification for recovery
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The Medium Energy Physics (MEP) group at Argonne National Laboratory invites applications for multiple experimental postdoctoral researcher positions. Depending on your background, your portfolio
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The Materials Science Division (MSD) of Argonne National Laboratory is seeking applicants for a postdoctoral appointee in experimental condensed matter physics. Although exceptional candidates in
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Argonne National Laboratory invites applications for the position of Group Leader for the Low-Energy Nuclear Physics Research Group (LER) within the Physics Division. LER is the largest research
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Argonne National Laboratory, in the Applied Materials Division, has an immediate opening for a postdoctoral appointee. The candidate will develop physics-based models to predict the structure and
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Argonne National Laboratory invites applications for the position of Director for the Materials Science Division (MSD), a core research division within the Physical Sciences and Engineering
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materials. The focus is to develop novel electrochemical deposition methods, control interfacial reaction kinetics, and engineer functional coatings and thin films. Advanced process design and optimization