192 structures-"https:"-"https:"-"https:"-"https:"-"https:"-"CEA-Saclay" Postdoctoral positions in United States
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structured and unstructured datasets such as multimodal data and remote sensing data. • Ability to engage effectively with stakeholders through outreach, extension, and engagement activities. Overtime Status
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Requisition Id 15537 Overview: We are seeking a Postdoctoral Research associate in computational nuclear physics. This position focuses on nuclear theory with an emphasis on nuclear structure and
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, especially surface holography, and their application to elucidate the spatiotemporal structure of nanostructures at surfaces and interfaces. The coherence-based probes will align with the capabilities promised
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total X-ray scattering (TXS) and pair distribution function (PDF) analysis capabilities and methodology to study laser-driven structural dynamics in functional materials. This position is part of a
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-doctoral fellow will conduct research under the supervision of Prof. Inas Khayal. The lab utilizes systems modeling and data science methods to develop an understanding of the structure and behavior
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the fundamental mechanisms of ion channels in excitable membranes using a multidisciplinary approach. Our NIH-funded research integrates structural biology, chemical biology, genetics, fluorescence microscopy, and
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studies (e.g., EELS, EDS) to probe defect structures and dynamics Apply advanced image processing and analysis; develop AI/ML workflows for quantitative defect characterization Implement high-throughput and
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
-state physics, ferroelectrics and/or 2D materials. Strong background in developing and/or applying materials simulation methods, such as atomistic simulations using electronic-structure and/or machine
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Electrochemical Mass Spectroscopy (DEMS), and complementary methods Perform electrochemical testing and benchmarking; analyze and interpret complex datasets to elucidate catalytic mechanisms and structure–property
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to Computational Fluid Dynamics. Mathematical topics of interest include structure-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and