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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 1 hour ago
the statistical agency within the U.S. Department of Energy (DOE). It collects, processes, analyzes, and publishes data to inform the economic activities of the American people and policymaking by DOE
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instrumentation (single-cell mass spectrometry, high-resolution microscopy, next-generation sequencing) and artificial intelligence-guided computational workflows. Job Description Develop computational image
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solidified artificial intelligence (AI) as a key science accelerator, especially in concert with automated techniques for sample creation, movement, and evaluation. However, the flexibility and intelligence
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of physics‑informed control of mobile manipulators, data collection from real and simulated machines, and model development and testing in simulated environments. The project offers close collaboration with
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demonstrated experience in qualitative data collection and analysis and analysis of survey data, with a preference for candidates with a strong commitment to community-engaged and policy-oriented scholarship
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and Responsibilities: Prepare technical documents, including formal project reports and scientific papers. (40%) Conduct laboratory and field data collection, with possible travel. (35%) Design and
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studies of physics‑informed control of mobile manipulators, data collection from real and simulated machines, and model development and testing in simulated environments. The project offers close
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tree-lined campus in Houston, Texas, Rice University is ranked among the nation's top 20 universities by U.S. News & World Report. Rice has a 6-to-1 undergraduate student-to-faculty ratio, and a
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analyze samples collected Develop new techniques as appropriate for project Functional Area 3: Research and Data Analysis Percent Effort: 40% Analyze water quality data Submit data to a data manager in a
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impairing cilia formation or function cause >35 severe human diseases (ciliopathies), collectively affecting 1 in 400 people with pleiotropic and overlapping phenotypes. The primary methodologies that you