48 computational-physics-"https:"-"https:"-"https:"-"Grenoble-INP" Postdoctoral positions at Oak Ridge National Laboratory
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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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to communicate research results through reports, publications and presentations. Experience in accelerator physics, including working in a control room, conducting accelerator-based experiments, and computational
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Program (DOE IP) to advance the chemical processing of unique f-element isotopes, including Cf-252, Bk-249, Es-254, Fm-257, and Pm-147. A core focus of the DOE IP is to improve and develop novel chemical
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Design Group in the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL). This position lives in the Alloy Behavior and Design Group
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.) to enable real-time process monitoring of the Directed Energy Deposition (DED) printing process. A background in sensors, instrumentation, and data analytics is preferred. Strong communication and program
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challenges facing the nation. The Computational Coupled Physics (CCP) Group within the Computational Sciences and Engineering Division (CSED), at Oak Ridge National Laboratory (ORNL) is seeking a Postdoctoral
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iterative solvers. Successful applications will work in applications related to gas dynamics, plasma physics, and radiation transport. The position comes with a travel allowance and access to advanced
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in ORNL’s Center for Radiation Protection Knowledge (CRPK). The candidate will work with experts in computational radiation dosimetry and risk assessment. The candidate should be an independent thinker
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to Computational Methods for Data Reduction. Topics include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a
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physics (HEP) detectors, neuromorphic computing, FPGA/ASIC design, and machine learning for edge processing. The successful candidate will work with a multi-institutional and multi-disciplinary team