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Skills General office suite and willingness to learn lab specific programs Supervisory Responsibilities No Required operation of university owned vehicles No Does this position require direct animal or
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Experience in machine-learning modeling for solid mechanics applications Experience in the development and coupling of numerical methods for solid mechanics modeling Experience in digital rock technology
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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Hamburg, ESRF in Grenoble and others) analysis of the experimental data, ideally connecting to our machine learning tools presentation of scientific results on conferences and in publications supervision
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
to do so. Minimum Education and Experience Requirements Applicants should have (or expect to receive before the start of the position) a PhD in Computer Science or EE/ECE on a topic in machine learning
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Pediatrics Postdoc Appointment Term: 2 year Appointment Start Date: Open position How to Submit Application Materials: https://forms.gle/xuUxLuwf4cTcBvWs9(link is external) Does this position pay above the
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Expertise in machine learning, including building and deploying prediction models Strong data science coding skills in programs and languages such as Python, R, Stata, and SQL Experience with research in
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fields. Applicants should have a range of quantitative skills including graduate-level knowledge of spatial data analysis, data management, statistics, and machine learning/computer vision. Advanced
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designing machine learning pipelines, building web applications or tools, and creating and maintaining visualization dashboards. Trainees should be comfortable with: · SQL, R, and Python