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Details Title Postdoctoral Fellowships in Networking Support for Machine Learning School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Computer Science Position
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computational skills and expertise in causal inference or network science are desired but not required. Start date and term are negotiable. Additional Qualifications Special Instructions For more information
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; distributionally robust optimization; 2) Graph Neural Networks, Large Language Models (LLMs), and geometric deep learning; and 3) federated learning and privacy preserving computing. Basic Qualifications Candidates
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Health, is responsible for the design, monitoring and statistical analysis of clinical trials and observational studies for several major national and international NIH-funded clinical research networks
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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
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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network engineering and angiogenesis 3). Applications of machine learning in cell and tissue engineering Candidates should have demonstrated publication records in cardiac and vascular engineering or
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modeling preferred. Sociology: PhD in Sociology or Organizational Behavior with expertise in computational social science, organizational theory, social networks, science and technology studies, or economic
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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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School fosters bold new ideas and collaborative learning networks that shape the future of business. Job Description Job Summary: The Digital, Data, and Design (D³) Institute at Harvard is accepting