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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 10 hours ago
carbon-cycle modeling. The project will build a unified modeling framework that uses GEDI LiDAR and Landsat/HLS data to train deep learning models capable of predicting forest structure variables such as
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Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty mentor
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excellence in education are encouraged to apply. PhD is required. Applicants must apply online at https://puwebp.princeton.edu/AcadHire/position/37861 and include curriculum vitae, research statement and names
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Science, Computer Science, Data Science, Neuroscience, or a related field by the start date. Demonstrated expertise in computational modeling of human behavior or computer vision / machine learning
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victim status, ethnicity, familial status, gender and/or gender identity or expression, marital status, military status, national origin, parental status, partnership status, predisposing genetic
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excellence, as evidenced by a strong publication record in one or more of the following areas: random matrix theory, stochastic processes, neural networks, machine learning, and sparse data structures
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or more projects, learning advanced cellular and molecular biology and anaerobic microbiology techniques. The candidate’s day will be split between benchwork to generate data, and computer work to generate
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access to various professional development opportunities, including a membership to Academic Impressions, LinkedIn Learning, and UT Dallas Bright Leaders Program. Visit https://hr.utdallas.edu/employees
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of Engineering, located in Brooklyn, NY, is deeply committed to excellence in teaching and learning. Tandon fosters student and faculty innovation and entrepreneurship that make a difference in the
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the university. Depending on interests and feasibility, they may be able to teach and/or engage in off-campus fieldwork with Professor Bezner Kerr. Anticipated Division of Time The successful candidate will split