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languages such as R, Python, Matlab. Familiarity with software development best practices (e.g., unit testing, version control). Familiarity with inferential statistics and machine learning. Expertise in
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-constrained machine-learning (ML) models in simulations of turbulent flows. You are expected to contribute to research and development in data-driven methodologies for turbulence modeling in LES (i.e., wall and
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to formulate mathematical models of the problems and develop efficient solution methods, particularly by leveraging techniques from machine learning and operations research. b) The applicants are expected
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) Limited until: 30.04.2032 Reference no.: 5022 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique balance of freedom and support. Join us if you’re passionate
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to 8 hours/day, lifting <30 lbs, may view computer up to 8 hours/day. Shift Generally Monday – Friday, 8a-5p with some flexibility Job Summary This position is designed to have 70% clinical time, 15
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service, or genetic information in its administration of educational policies, programs, or activities; admissions policies; scholarship and loan programs; athletic or other University-administered programs
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 16 hours ago
, graduate students, and recent graduates to learn about policy analysis projects across various focus areas. These areas include Domestic Energy Policy, Power Sector, Critical Minerals and Materials
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calculations, sample size determinations and statistical analysis plan. 3. Apply machine learning approaches to integrate diverse datasets collected from study participants to identify subtle differences
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modeling. Brief Description of Duties: The Postdoctoral Associate will assist the Principal Investigator Dr Fang Luo in the Department of Electrical and Computer Engineering . The incumbent will conduct
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learning environments that are free from harassment and prohibited discrimination. Duke prohibits discrimination and harassment in the administration of both its employment and educational policies. Duke