15 programming-"https:"-"https:"-"Data-driven-Materials-Modeling" Postdoctoral positions
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activities and data-driven predictive modeling for precision medicine. In addition to our core research questions and mission, the unit will also serve as a nexus between multiple branches and divisions and
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The Ohio State University | 2 months ago
analysis, machine learning, and data-driven modeling applied to large astronomical datasets and time-domain surveys is highly desirable. Although experience with microlensing and transit exoplanet
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The Ohio State University | 2 months ago
skills using modern languages such as Python or C++. Expertise in statistical analysis, machine learning, and data-driven modeling is highly desirable. Appointment is contingent on the university’s
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materials characterization Strong background in computational materials science and machine learning applications Proficiency in programming and data analysis languages (LabVIEW, Python, MatLab, OriginPro
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contacted prior to receiving the candidate’s consent to contact. Upload all materials via https://utah.peopleadmin.com/postings/ . Candidates may be asked to provide additional information during the
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Innovation: https://reporter.nih.gov/project-details/11294051 · WONDER: Accelerating Real World Data-driven Precision Oncology through Data Science and Informatics Excellence in Research: https
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fundamental Earth science and engineering applications . Research activities may involve geophysical forward modeling, AI-driven geophysical inversion, seismic monitoring and imaging, scientific machine
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fundamental Earth science and engineering applications . Research activities may involve geophysical forward modeling, AI-driven geophysical inversion, seismic monitoring and imaging, scientific machine
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statistical modeling. Experience working with large, complex, and multi-dimensional datasets. Experience with spatial analysis and geospatial data integration, including use of GIS tools (e.g., ArcGIS
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statistical modeling. Experience working with large, complex, and multi-dimensional datasets. Experience with spatial analysis and geospatial data integration, including use of GIS tools (e.g., ArcGIS