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Field
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, embracing failure as a learning opportunity, and continuously enhancing our knowledge and methods to tackle local, national, and global challenges. The postdoctoral associate will work directly with both
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-making. Among the key duties of this position are the following: Develop and refine computational models (e.g., mechanistic, machine learning, or hybrid approaches) for ICU patients. Integrate and analyze
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), supernovae, gravitational wave sources, magnetic activity in exoplanets, and machine learning classification. The candidate will lead and participate in observations and data analysis of these sources in all
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PhD in Data Science, Computational Social Science, Computer Science, or Information Science. The position requires experience with at least one of the following: Data Science, Machine Learning
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chemical discoveries for renewable energy, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing
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to systematically understand cancer biology, identify diagnostic and prognostic biomarkers, and improve cancer therapy. Projects will involve the development of AI solutions, including machine learning, deep learning
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cognitive, clinical, genetic, and proteomic data and manages them in the data repository and computer servers. Runs existing PET/MR brain image processing pipelines on the computer servers, produces
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the staff performance management system. Physical Requirements (With or Without Accommodations): • Visual acuity to read information from computer screens, forms and other printed materials and information
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. Program Contact Want to learn more about the MLEF Program? Register for one of our information session s. Visit our website www.energy.gov/fe/mlef for more information on the MLEF Program. Contact MLEF
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and stochastic analysis, numerical analysis, and scientific machine learning. Interest in interdisciplinary efforts is also valued. Commitment to and experience in teaching and mentoring student