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Field
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of microfluidic devices. Simulation for microfluidics. (CFD) High Performance Computing and/or GPU programming for this domain. Machine learning algorithms for this domain Clean energy solutions (e.g., microfluidic
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
-year, time limited position with the possibility to extend to 2 years. This is a computational position that offers a collaborative opportunity between basic science (computational genome science) and
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(for example insect-eye–inspired motion detectors for planetary landing and insect-inspired navigation algorithms) to evolutionary and neuromorphic approaches to autonomous control, as well as soft-robotic
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Posting Details Posting Summary Working Title Adjunct Computer Science Instructor Role Title Adjunct Computer Science Instructor Role Code 01011-SW FLSA Exempt Pay Band Position Number Agency New
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PhD in Computer Science or Electrical Engineering with biomedical data analysis emphasis or related fields is required. Previous experience in developing novel data mining algorithm, magnetic resonance
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understanding of computational algorithms and statistical modeling and a working knowledge in molecular biology, microbiology, and microbial ecology • possess a working knowledge on genomic sciences and
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the world) and present your work at top-notch conferences and journals in our domain. You should have completed your Master/Diploma studies with top grades in Computer Science, Artificial Intelligence
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be achieved, for example, by developing learning algorithms and bringing together different sensor systems in the vehicle and on the road. Where you put the focus - that is up to you. The concepts
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investigation and developing software algorithms and techniques to support human or machine information interactions for the purpose of information retrieval/dissemination, analysis and/or decision making
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, randomized data structures, high-performance computing, and quantum algorithms. Beyond this research, we aim at supporting computational thinking and computational problem-solving in the Earth sciences