1,743 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" research jobs
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combinations of structural and functional properties, using both simulations for machine learning and experimental validation. Fabrication tools and methods are already established in our laboratory. Key
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experiential learning courses, as well as contributing lectures to core plant pathology courses that support required and elective curricula in the Undergraduate Program in Plant Science and Graduate Program in
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website (http://www.mouncelab.com). Experience in molecular virology is preferred but not required. Responsibilities are flexible according to discussions between the applicant and the PI.Interested
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science methodologies (e.g., machine learning). Experience working with large-scale environmental and remotely-sensed datasets, strong proficiency in R and version control tools (such as GitHub), and
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silico identification of candidate developmental pathways explaining tradeoff variation. Contribute to advanced statistical analyses and interpretable machine learning approaches (in collaboration with
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in Singapore alongside DSO National Laboratories, Defence Science and Technology Agency (DSTA), Temasek Laboratories @ NUS and @SUTD and the local defence industry. For more details, please view https
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position within a Research Infrastructure? No Offer Description Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the
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, or similar) will be valued; 9) Experience in machine learning techniques applied to materials science or process engineering (regression, classification, optimization, predictive models) will be valued; 10
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interests in applied statistics, machine learning, or computational biology are encouraged to apply. For more information, please visit our website https://ds.dfci.harvard.edu/postdocs to view the list
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago
to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning