80 operations-"https:"-"https:"-"https:" Postdoctoral positions at Oak Ridge National Laboratory
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Laboratory (ORNL). The selected candidate will work in a highly collaborative environment, leveraging state-of-the-art neutron and X-ray characterization facilities to develop a mechanistic understanding of
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. Demonstrated programming ability and knowledge of Python and/or C++. Experience with deep learning frameworks like PyTorch and application on high-performance computing (HPC) environments using distributed data
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to maintain high scientific productivity and achieve project objectives. Communicate and coordinate with operations and technical staff to support successful project execution. Ensure compliance with
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modeling and networked biological systems. You will work at the intersection of high-performance computing (HPC), computational biophysics, and machine learning, leveraging leadership-class computing
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Requisition Id 16262 Overview: We are seeking a postdoctoral researcher to work at the intersection of tensor networks, quantum algorithms, scientific computing, topological physics, and quantum
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Maintain strong commitment to the implementation and perpetuation of ORNL core values and ethics Postdoctoral research associates are required to work onsite at ORNL’s campus. Deliver ORNL’s mission by
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equal opportunity by fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A Ph.D. in material science, or closely related field with
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-Performance Computing (HPC), scientific Artificial Intelligence (AI), and scientific edge computing. We are a leader in computational and computer science, with signature strengths in high-performance computing
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with the Multiscale Dynamics and Heterogeneities in Quantum Materials themes at the CNMS and US DOE’s Genesis projects. The candidate is expected to work closely with Soumendu Bagchi and P. Ganesh. As
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Postdoctoral Research Associate- AI/ML Accelerated Theory Modeling & Simulation for Microelectronics
length/time scales, to provide improved mechanistic insights into nanomaterials response. Bulk of the work will be on novel materials for next-generation microelectronic devices (e.g. oxide ferroelectrics