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field completed within the last five years. Good track record in scattering theory, quantum many-body theory, thermodynamics, statistical mechanics, or non-equilibrium physics. Experience in
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/ML techniques for real-time, real-world data Transport and dispersion modeling Fate modeling of materials in the atmosphere Applied statistics Data analytics Deliver ORNL’s mission by aligning
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scattering and urban science—to apply and evaluate research methods on large, domain-specific scientific datasets. Major Duties/Responsibilities: Designing and developing foundational statistical/AI/data
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, and statistics. Motivated self-starter with the ability to work independently and to participate creatively in collaborative teams across the laboratory. Ability to function well in a fast-paced
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. Strong experience in using techniques or tools relevant to scientific visualization, ML/AI, HPC, and statistics. Motivated self-starter with the ability to work independently and to participate creatively
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Science, Computer Science, Applied Mathematics and Statistics, Electrical and Computer Engineering, Biomedical Engineering, or a related field. Experience with a deep learning framework like PyTorch. Strong
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relevant to grid resilience and equity analysis. Apply statistical techniques and machine learning algorithms to identify patterns and trends related to infrastructure vulnerabilities, social vulnerabilities
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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