63 systems-engineer-"https:"-"https:"-"https:"-"https:"-"https:" Postdoctoral positions at Argonne
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This position will be dedicated to research projects aiming to unravel the fundamental interfacial processes in membrane and ionomer materials employed in energy conversion systems such as critical
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The Surface Scattering and Microdiffraction (SSM) group in the X-ray Science Division (XSD) at the Advanced Photon Source (APS), Argonne National Laboratory is seeking Two Postdoctoral Appointees
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The Coherent and Ultrafast X-ray Science Group in the Materials Science Division at Argonne National Laboratory is seeking a highly motivated postdoctoral appointee to lead research in ultrafast
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, distributed systems, or large-scale data pipelines Experience with game engines, XR systems, or advanced graphics frameworks applied to scientific data Record of publications in visualization, AI
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activities. This is an exciting opportunity to work within a collaborative group with deep expertise in silicon detectors, Trigger/DAQ (TDAQ) systems, software, and computing. The Argonne ATLAS group plays a
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The Applied Materials Division (AMD) at Argonne National Laboratory is seeking a Postdoctoral candidate in the area of organic chemistry with focus on battery electrolyte materials. This position
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Argonne National Laboratory in the Applied Materials Division (AMD) at is seeking a Postdoctoral candidate in the area of organic chemistry and electrochemistry with focus on battery electrolyte
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The Materials Science Division is seeking a highly motivated Postdoctoral Research Associate to join our Quantum States and Crystalline Matter Group. This exciting research opportunity focuses
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that influence the development, intensification, and persistence of extreme events, using observational datasets, machine learning, and Earth system modeling. The successful candidate will work with observational
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-based and AI/ML approaches. This position focuses on high-resolution Earth system modeling and the analysis of convective storms and weather and hydrological hazards to improve predictability