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data sets (genomics, proteomics, imaging, neuroscience), and related areas at the interface of computer/data science and the life sciences. Applicants must hold a Ph.D. in Engineering, Computer
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(e.g., tensor or multi-modality data). Work with other researchers and PhDs to develop AI applications related to image processing, computational imaging as well as computer vision. Lead a team of junior
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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 7 hours ago
that includes offices, classrooms, a large lecture hall, computer laboratories, a Student Learning Commons and Success Center, and a state-of-the art Simulation Learning Center. Through the use of simulation, we
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of Electrical and Computer Engineering within the Jacobs School of Engineering at UC San Diego is conducting an open search for a non-tenure track Assistant Project Scientist for 2 positions. 1)The successful
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of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7 master students. Computing time is available on our local cluster and on the Austrian Scientific Cluster, a supercomputer
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PhD student will expect to develop some experience in developing power systems models using a range of computer languages and tools (e.g. Python, MATLAB, OPNET, etc), ideally for applications involving
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contribute to the PhD program in material science and engineering. The position offers opportunities for interdisciplinary collaboration, including partnerships within the department and across other research
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institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Computer Vision offers two full-time positions as Research Associate / PhD Student (m/f/x
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knowledge, communication, organization, computer skills), and work experience; highlighting experience in research data management, data curation, and application of FAIR principles; More information https
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contribute to the PhD program in material science and engineering. The position offers opportunities for interdisciplinary collaboration, including partnerships within the department and across other research