60 computer-science-intern "https:" "https:" "https:" "https:" "DESY" research jobs at Oak Ridge National Laboratory
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analysis necessary for simulating and understanding complex, multi-scale systems. The group is part of the Mathematics in Computation (MiC) Section of the Computer Science and Mathematics (CSM) Division. CSM
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through papers, artifacts, and presentations at top-tier venues. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, a physical/computational science discipline (e.g., physics, chemistry
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Qualifications: Ph.D. in electrical engineering, computer science, or related discipline completed within the last five years. Demonstrated expertise in computed tomography (CT), with experience in sparse-view and
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physics, materials science, applied mathematics, computer science, or a related field, and no more than five years of experience beyond PhD. Preferred Qualifications: Background in quantum magnetism
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through the High Flux Isotope Reactor, the Radiochemical Engineering Development Center, ORNL's other nuclear facilities, and an assemblage of world-leading scientists and engineers. Please visit https
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workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in evolutionary biology, plant biology, genomics, bioinformatics, mathematics, statistics, computer
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‑correction, calibration, and adaptive data‑acquisition methods to improve measurement efficiency and throughput Apply physics‑based or computational transport modeling to interpret internal material gradients
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challenges facing the nation. We are seeking a Postdoctoral Research Associate who will support the Quantum Sensing and Computing Group in the Computational Science and Engineering Division (CSED), Computing
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), Energy Science and Technology Directorate (ESTD), at Oak Ridge National Laboratory (ORNL). Major Duties/Responsibilities: Develop physics-based computational models, including Finite Element Analysis (FEA
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Postdoctoral Research Associate in the areas Artificial Intelligence (AI) for Integrated Hydrology Modeling. The successful candidate will have a strong background in computational science, data analysis, and