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, machine-learning interatomic potentials, or related scientific machine-learning methods for atomistic systems. Familiarity with uncertainty quantification, active learning, Bayesian optimization, agentic
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Mathjobs.org | about 1 month ago
, uncertainty quantification and probabilistic methods, and integrating any area of mathematics research and AI. The successful candidate will be expected to develop a leading research program, contribute to
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, uncertainty quantification and probabilistic methods, and integrating any area of mathematics research and AI. The successful candidate will be expected to develop a leading research program, contribute to
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MOHAMED BIN ZAYED UNIVERSITY OF ARTIFICIAL INTELLIGENCE | Dhabi Kalan, Haryana | India | about 2 months ago
inference, uncertainty quantification, fairness, and interpretability in AI. We encourage interdisciplinary research, integrating statistical innovation with decision sciences, healthcare, climate science
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, MATLAB or scientific simulation codes. Experience in reduced-order models, scientific AI, uncertainty quantification or digital twins. Scientific publications and participation in R&D projects. Ability to
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Biophysical and Biomedical Measurement Group - NIST | Gaithersburg, Maryland | United States | about 1 month ago
radiotherapy-relevant measurements. - Experience with statistical analysis, dose-response modeling, signal processing, internal standards/calibration, and uncertainty quantification. - Experience with
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inverse problems Expertise in sensitivity analysis and uncertainty quantification for digital twins Enjoyment of scientific work and working with students Independent and autonomous working style
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quantification through spike-ins; multi-omic datasets), microbial phylogenetics, variable importance, model selection, trait prediction, and uncertainty quantification. Substantial professional development
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environment on scientifically challenging problems Hands-on experience with ML/DL workflows and common software libraries Experience with statistical machine learning, including uncertainty quantification
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scientific machine-learning methods for atomistic systems. Familiarity with uncertainty quantification, active learning, Bayesian optimization, agentic AI, or closed-loop materials discovery. Experience in