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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
the start date, a PhD in Data Science, Computer Science, Electrical Engineering, Electrical and Computer Engineering, or a closely related field. The applicant’s research should focus on machine learning
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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with experts in AI and machine learning. The post-doctoral associate will also be responsible for data management and dissemination of scientific results. The successful candidate will join a
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). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology
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). Experience with human-factors instrumentation and data streams: eye tracking, physiological sensors, and motion capture. Familiarity with data/video coding tools and computer vision (e.g., OpenCV, scikit-learn
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AgriLife is uniquely positioned to improve lives, environments and the Texas economy through education, research, extension and service. Click here to learn more about how you can be a part of AgriLife and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 16 hours ago
Carolina and beyond. Education: We prepare tomorrow`s healthcare professionals and biomedical researchers from all backgrounds by facilitating learning within innovative and integrated curricula and team
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://news.vt.edu/articles/2023/10/eng-futuregaward.html Required Qualifications ● Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field. ● PhD must be awarded
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written Communication Skills. Certificates/Credentials/Licenses M.D. or PhD Required Computer Skills General office suite, GraphPad-Prism, Endnote, Snapgene, and willingness to learn lab specific software
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that can be repurposed for viruses with pandemic potential. This includes working closely with computer scientists to utilize published “omics” datasets and machine learning approaches to identify FDA