147 machine-learning-"https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" Fellowship research jobs at Harvard University in United States
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computational models of vision and machine learning methods (for example CNNs, deep generative models, encoding models) is preferred but not required Ability to communicate scientific results clearly through
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Description The Procaccia Group (https://procaccia.info/) at the John A. Paulson School of Engineering and Applied Sciences (SEAS) at Harvard University is seeking a postdoctoral fellow to work on economics and
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] Subject Areas: high-dimenstional statistics, Machine Learning theory, Mathematical foundations of AI Appl Deadline: none (posted 2026/03/06 05:00 AM UnitedKingdomTime) Position Description: Apply Position
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about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https://www.shih.hms.harvard.edu/ . What you’ll do: Develop DNA-based sensors that seed crisscross assembly of single
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protein coding genetic association data with functional and machine learning-derived features 4. Developing methods to characterize the genetic architecture of autism Salary and Benefits This position is
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projects, as well as in multiagent systems, including computational game theory, security games, machine learning in multiagent settings, automated planning under uncertainty, social networks and others
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or qualification, field of scholarship, and accomplishments in the field. Create a Job Match for Similar Jobs About Harvard University Harvard University is devoted to excellence in teaching, learning, and research
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position in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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academic calendar, looking at 2026-2027 dates: https://registrar.fas.harvard.edu/calendars#tenyear). Applicants may consider an early September start date, or a late January start date, for shorter
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PhD, and benefits can be found at https://postdoc.hms.harvard.edu/guidelines . With this appointment, you are represented by the Harvard Academic Workers (HAW) – UAW for purposes of collective