129 machine-learning "https:" "https:" "https:" "https:" "https:" Fellowship positions in United States
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solver who wants to be part of a dynamic team. Information about the Church Lab: Learn more about the innovative work led by Dr. George Church here: https://churchlab.hms.harvard.edu/ , https
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. Experience in, or willingness to learn data-driven approaches, including artificial intelligence (AI) and machine learning (ML) models, to solve problems. The Successful Candidate Will A curious scholar with a
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at finale.seas.harvard.edu and our group’s webpage https://dtak.github.io/ We work on probabilistic models, reinforcement learning, and interpretability + human factors. Basic Qualifications Candidates are required to have
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solver who wants to be part of a dynamic team. Learn more about the innovative work led by Dr. Don Ingber here: https://wyss.harvard.edu/technology/human-organs-on-chips/ What you’ll do: Independently
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dental care programs, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at: https://hr.duke.edu/benefits/ Equal Opportunity
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technological change driven simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic, and human data, and a new emphasis on the importance
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on developing robotics and cyber physical systems solutions using machine learning and artificial intelligence to support different aspects of marine science, with opportunities to expand to other areas
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insurance, generous paid leave and retirement programs. To learn more about UofSC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Research Grant or Time
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reproducible analysis workflows Familiarity with computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability
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scientists, biomedical informaticians, clinicians, and public health researchers to develop deployable, trustworthy methods that improve patient outcomes and health system operations. Key responsibilities