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to manage multiple projects in a fast-paced environment. • Strong teamwork and collaboration skills. • Competency in statistical analysis tools (e.g., SAS, R, XLstat, Multivariate analysis). • Proficiency in
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U.S. Department of Energy (DOE) | Washington, District of Columbia | United States | about 18 hours ago
Scholars Program, visit https://orise.orau.gov/doescholars or contact us at doescholars@orise.orau.gov . The DOE Scholars Program offers multiple opportunities during the year to accommodate the needs and
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experience with MRI acquisition and reconstruction—particularly diffusion or dynamic imaging—is highly desirable, along with strong programming abilities in languages such as Python or MATLAB. Experience with
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evaluation, inter-reader agreement analysis, kappa statistics, and related assessment methods · Familiarity with model validation across multiple sites, scanners, or imaging vendors · Proficiency
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multiple access. The focus will be on the application of AI techniques, aiming at their reliable, robust, and effective integration. Requirements: - Experience with the Python programming language
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, or modeling using tools such as Python, R, GIS, or similar computational platforms. Demonstrated ability to collaborate across disciplines and translate technical and social science insights into scholarly
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computational algorithm(s), perform data analysis, collaborate with biologists and physicians. He or she will lead multiple projects, work in a multidisciplinary environment and present/publish the results in
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of project results analyse climate-induced changes on arctic tundra and related fire regimes by conducting factorial experiments using multiple climate-change scenarios. Requirements: a PhD in biophysical
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 9 hours ago
) working groups) to investigate how symbology behaves under multiple overlapping data layers, varying background conditions, and operational display constraints, and to translate these findings
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highly multidisciplinary, looking at infectious diseases through multiple perspectives, multiple scales and multiple data streams. We work closely with a network of collaborators and public health agencies