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University of North Carolina Wilmington | Wilmington, North Carolina | United States | about 2 months ago
undergraduate and 89 graduate majors. The department operates successful Ph.D. programs in Clinical Psychology, Psychological Science, and Applied Behavior Analysis and a Neuroscience & Behavior Master’s program
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
support a rich array of outstanding health sciences research programs, centers and resources. We provide infrastructure and opportunities for collaboration among disciplines throughout and beyond our
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first experiments of the future quantum-computer technology that is orders of magnitude more efficient than existing quantum processors. Join us in shaping the future! As a result of five ERC grants
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estimate for this position is $66,737.00 - $77,030.00. See Table https://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-oct-2025-scales/t23.pdf Application Window Open date: July 25
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release time and tuition assistance for completing a degree while a Texas A&M employee Living Well, a program at Texas A&M that has been built by employees, for employees All positions are security
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of scientific programming language(s), computer simulation, and quantum computing algorithms All tasks and job responsibilities must be performed safely without injury to self or others in compliance with System
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on the basis of sex in the education program or activity that it operates, as required by Title IX and 34 CFR part 106. The requirement not to discriminate in education programs or activities extends
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; developing visualisation prototypes to communicate uncertainty to end-users; contributing to a computational framework for data production in cooperation with Research Software Engineers; working closely with
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, computational, and machine learning/AI methods, with a particular emphasis on deep learning approaches improve our understanding and prediction of infectious disease dynamics. Projects are also strongly grounded