186 high-performance-quantum-computing Fellowship research jobs at Harvard University
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Details Title Postdoctoral Fellowship in Computer Science - Programming Languages and Artificial Intelligence School Harvard John A. Paulson School of Engineering and Applied Sciences Department
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Details Title HMS - Postdoctoral Fellow in Biomedical Informatics School Harvard Medical School Department/Area Position Description The Farhat Lab in the Department of Biomedical Informatics is
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to appoint one or more postdoctoral fellows beginning in November/December 2025. We are looking for candidates with interests in the use of atomic cavities and atomic arrays for quantum computing. Candidates
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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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applications for a Postdoctoral Fellow with Professor Pragya Sur. Professor Sur’s lab focuses on research in high-dimensional statistics, machine learning theory, or more broadly, mathematical foundations of AI
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(D^3) Institute and the LISH/Data Science & AI Operations Lab seek enthusiastic Postdoctoral Fellows skilled in computer science, statistics, operations research, or related computational fields. As
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dynamics, using an array of methods including natural language processing and experiments. This is a two-year position (one-year contract renewable based on performance). The primary criterion for acceptance
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Director of LISH (Dr. Ramona Pop). The position involves conducting rigorous empirical research using field experiments, large-scale data analysis, and computational methods to advance our understanding
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dynamics, using an array of methods including natural language processing and experiments. This is a two-year position (one-year contract renewable based on performance). The primary criterion for acceptance
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cutting-edge theories, methods, and computational tools for integrating large-scale, heterogeneous biomedical data across multi-institutional research networks, with a focus on the analytical and