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develop statistical, mathematical, causal-inference, simulation, and machine-learning methods using large-scale flight trajectory and operational datasets. Research may cover airport surface congestion
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of cattle and swine semen samples placed under the stress of cryopreservation. Learning objectives: You will learn or enhance your current skillsets in the following: Proficiency in genetic diversity analysis
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differential geometry, algebraic geometry, etc.) or for computer science (such as machine learning, linear logic, etc.). While the position start date is flexible, the successful applicant must have completed
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including historical linguistics, semantics, pragmatics, computational linguistics, phonology, or sociolinguistics. We would like to see candidates who can communicate with and learn from both linguists and
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training, travel to communicate findings, and professional networking will also be available. Learning Objectives: Under the guidance of a mentor, you will have the opportunity to learn to: (a) plan, execute
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crop area and learn basic agronomic, data collection, and plant breeding methodologies in trials and nurseries planted at the USDA-ARS. Learning Objectives: The project assignments will provide you with
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, Physics, Computer Science, or a related discipline. Demonstrated research experience in computational chemistry, atomistic simulations, machine learning, or artificial intelligence for materials and
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safe environment, and everything within walking distance. Spectacular outdoor activities await right at the doorstep. If you are looking for an exciting opportunity and would like to learn more about
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science, machine learning, AI, or any computational science discipline of interest to the Computing Sciences Area and Berkeley Lab. Fellows apply advances in these fields to computational modeling
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Schemes of Service: Research Division: Engineering Employment Type: Fixed Term As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will