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and experience in natural language processing, machine learning, and deep learning. • Strong written and oral communication skills in English. • Ability to work independently and as part of a team
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 months ago
, and public service. Position Summary Develop highly curated datasets of chemical bioactivity and build statistically validated and externally predictive machine learning models of these activities
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. Mathematical techniques include qualitative and numerical analysis of deterministic and stochastic dynamical systems, optimal control, network models, and machine learning. Preference will be given to candidates
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machines that both learn from humans and help humans learn. The postdoctoral fellow will lead a project using AI technologies to support active learning in young children, by empowering them to create
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD (or foreign equivalent) in Biomedical Engineering, Medical Physics, Electrical, Computer Engineering or a
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external) How to Submit Application Materials: To begin the application process, please send an email using the subject line “Postdoctoral Position in Machine Learning for Advancing Mental Health” to Tina
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compensation package. This tool takes into account all of the benefits that you are eligible for, including health insurance, retirement plans, and paid time off. To access this tool and learn more about the
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integrated circuits (IC) and printed circuit boards (PCB). Additionally, the candidate should demonstrate expertise in applying computer vision, image analysis techniques, machine learning, deep learning to IC
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Alexandria, Virginia. The focus of these positions will be on quantum computing, quantum algorithms, quantum learning, quantum error correction, and quantum fault-tolerance. The successful candidate will join
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI