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Field
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, inverse problem, machine learning Expertise in the analysis of a wide range of geospatial and geodetic data sets Strong expertise in programming with Python or MATLAB As position requires stakeholder
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Engineering, Biomedical Engineering, Information Systems, Artificial Intelligence or related areas that demonstrate a solid computational base; Candidates enrolled in a non-degree course: Candidates who exceed
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, at the time of application, a bachelor's degree in Computer Engineering, Biomedical Engineering, Computer Science, Artificial Intelligence, Data Science or related areas that demonstrate a solid
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mathematics, computer science, electrical engineering, machine learning, optimization, statistics, etc.) and specific domain area. Finalists will be paired with mentors by the search committee, facilitating a
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closely related field (e.g. Chemistry, Physics, Biophysics, Biochemistry, Molecular biology, etc) Computer Skills Academic and research software relevant to job duties (Linux operating system, Gaussian/ORCA
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and algorithm development, modeling machine learning, and scientific simulation Ability to work well in an interdisciplinary environment, and to collaborate with experimentalists Strong oral and written
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analysis, software and algorithm development, modeling machine learning, and scientific simulation Ability to work well in an interdisciplinary environment, and to collaborate with experimentalists Strong
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 21 hours ago
affiliations through creative programs, vibrant student organizations, and a living/learning environment built on core values and uncompromising principles. The Division is a leader and primary spokesperson
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analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with staff and our current PhD students. PhD research fellows receive
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Work Location(s) Number of offers available1Company/InstituteDepartment of Electrical Engineering and Computer ScienceCountryNorwayGeofield Contact City STAVANGER Website http://www.uis.no Street 4036