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Requisition Id 17232 Overview: We are seeking a Postdoctoral Research Associate who will focus on applying computational methods in the areas of reaction chemistry in condensed phase systems
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eligible you must have completed a PhD in chemistry, physics, engineering, or a related field with in the last 5 years or expect to complete it by January 2027. Visa sponsorship is not available
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workflows. The successful candidate will develop novel AI methods that integrate scientific knowledge, simulation, experimental data, and large-scale computing to achieve measurable AI advantage in scientific
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accelerator-optimized methods — for large-scale numerical, scientific, and/or AI models. Demonstrating the scalability of new algorithms on leadership supercomputers for large-scale problems of national and
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workflows; document methods, prepare peer-reviewed publications and project reports, and present research results. Conduct experiments in accordance with ORNL laboratory and laser-safety procedures. Deliver
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data and develop data-driven methods for predicting land loss and ecosystem transitions in wetland-rich landscapes of the Gulf Coast with a focus on coastal Louisiana. This candidate will directly
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responsible for delivering high impact research on the development of novel molecules, materials, and methods for ion recognition and stimuli-responsive separations. You will work very closely with specialists
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, qualification, and deployment of AI agents and models, Computational Fluid Dynamics (CFD) simulation codes, and Finite Element Method (FEM) based tools for nuclear energy (fission and fusion) applications
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Qualifications: A PhD in Computational Chemistry, Physics, Chemical Engineering, Materials Science and Engineering, or a related field completed within the last 5 years Experience in theoretical and computational
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that have applications in multiple sectors of importance in the Department of Energy. The primary focus will be developing separation methods using mass spectrometry including microfluidics, MEMS, and mass