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Geosciences, Environmental sciences, Civil or Environmental Engineering, Physics or Mathematics or a related discipline Experience in programming (e.g., Python, MATLAB, or similar), interest in machine learning
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, societal, and scholarly sector. AI3 includes more than 70 faculty members with interests ranging from novel algorithms, architectures, and mathematical / ethical foundations to applications in art
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modeling of structural variability. The work may include inverse problems, regularization strategies, statistical modeling, representation learning, and geometric or variational approaches to volumetric data
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that the fellow will take ownership of a well-scoped research direction. Research activities may combine quantitative modeling and statistical analysis with literature synthesis, interviews, workshops, and other
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The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing
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or equivalent Skills/Qualifications What we expect A doctoral degree (PhD) in science, preferably in systems biology, bioinformatics, (bio)-statistics, (computational) biology, computer science, engineering
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ability to cultivate bacteria and fungi, to operate a plate reader and microscope; - the ability to perform statistical multivariate analyses of biological and chemical data; - the ability to operate
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display data for presentation in research conferences and for manuscript preparation; use graphics and statistical software to analyze and present data. 10% Supervise graduate students and other personnel
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publications Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of High Energy Physics Demonstrated excellence in physics analysis, including data analysis, statistical
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/ strongly correlated electrons/ Topology , Theory , Topology Statistical and Biological Physics / Statistical and Biological Physics , Statistical Physics Nuclear Physics / hadronic structure; Nuclear