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github.com/usnistgov/ThreeBodyTB.jl), cluster expansion, classical potential development, and machine learning. In addition to work on specific problems, I work on developing new first principles-based
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physical processes Familiarity with uncertainty quantification and statistical analysis Preferred Qualifications Experience integrating AI or machine learning approaches into environmental modeling
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a wide range of projects involving machine learning (ML) and artificial intelligence (AI), including autonomy, sensing and communication, and decision support systems, among others. The R&D Engineer
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modeling and in data science, machine learning, or artificial intelligence applied to geospatial data; Ability to teach undergraduate and graduate courses in areas of expertise and to teach statistical
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detection, waveform segmentation, feature extraction, hemodynamic modeling, time-series analysis, machine learning, and development of algorithms for real-world clinical data. The fellow will have the
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immediately available in Physics-informed Generative Modeling and Multiscale Learning. The successful candidate will work at the interface of physics-based modeling and probabilistic machine learning
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, Pharmacogenomics, and AI/Machine Learning Job Description: A Postdoctoral Research Associate position is immediately available for a highly motivated, independent, and ambitious candidate in the
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und Stellenangebote > Academic staff > Ph.D Position on Machine Learning in Biomechanics (m/w/d) Back to News Board Browse in News Professorship of Data-driven Materials Modeling Ph.D
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to accelerate predictions and for multiscale modeling via machine learning force fields. This research will focus on applying a range of computational tools to realistic material systems, including
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, combinatorial optimization or Bayesian network analysis Large language models or machine learning/predictive modeling for longitudinal data analysis Strong computer programming skills Strong mathematical