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machine learning and Bayesian calibration methods to enable multi-scale, multi-physics model development. Complete simulation verification, model validation, uncertainty quantification, and documentation
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-throughput phenotyping at ORNL's Advanced Plant Phenotyping Laboratory (APPL) with paired geochemical and microbial measurements. Utilize laboratory equipment and software that may include a Picarro gas
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, collaborate with interdisciplinary teams, publish in leading scientific venues, and contribute to emerging QHPC software and system technologies. Major Duties/Responsibilities: Develop and evaluate
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implementation of constitutive models within commercial and/or open-source finite element software is required. Preferred Qualifications: Demonstrated expertise in multi-physics FE simulations is preferred
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, quantify nonlinear interactions, and advance scientific understanding of coastal ecosystem resilience. Curate and develop reproducible AI-ready datasets, computational workflows, and research software
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related field completed within the last 5 years. Experience utilizing computational thermodynamic (CALPHAD) software, such as Thermo-Calc, DICTRA, PANDAT, or FactSage. Proficiency in materials data
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operational and application software; and educates and trains the next generation of computational scientists. A postdoctoral associate position is available immediately for candidates interested in and capable
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for extreme-scale, heterogeneous computing. This role sits at the intersection of compiler infrastructure, formal verification, runtime systems, and hardware/software co‑design—expanding into emerging paradigms
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Requisition Id 16736 Overview: We are seeking a Postdoctoral Research Associate who will work with a multi-disciplinary group of experts in economics, engineering, software development, and building
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/or machining process optimization Hands-on experience with CNC machine tools, machine controllers, G-code, CAM software, machining process planning, fixture design, and practical manufacturing