51 density-functional-theory-postdoc Postdoctoral positions at Oak Ridge National Laboratory
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Laboratory (ORNL). As part of our research team, you will closely collaborate with a team that includes condensed matter theorists, experts in neutron/X-ray scattering, and experts in thin film and single
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Postdoctoral Research Associate - Theory-in-the-loop of Autonomous Experiments for Materials-by-Desi
carlo), as well as experience in developing and/or applying advanced AI/ML methods to accelerate materials discovery. The project will involve integrating such theory-informed AI-models for creating
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Requisition Id 15764 Purpose The Glenn T. Seaborg Initiative (GTSI) of Oak Ridge National Laboratory (ORNL) is committed to enhancing and maintaining US capabilities in actinide science and
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needs as well as the proven ability to function well in a fast-paced environment. Postdocs: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must
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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
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relevance to clean energy, climate resilience, and infrastructure planning. Postdocs benefit from access to world-leading high-performance computing facilities and a deeply interdisciplinary research
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projects relevant to catalysis and critical materials. Contribute to methods development and integrate data science to accelerate simulations, analyze large datasets, and extract properties. Work in multi
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in the Materials Science and Technology Division (MSTD), Physical Sciences Directorate (PSD) at Oak Ridge National Laboratory (ORNL). The selected candidate will work with multiple other groups within
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compliance, reproducibility, and interoperability across scientific domains. By improving data readiness processes, this role will amplify the potential of AI-driven discovery in areas such as high energy
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strong background in quantum computing, computational physics, and a solid understanding of condensed matter quantum many-body theory. This position resides within the Quantum Computational Science group