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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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(e.g., MATLAB, R, or Stata); · Writing papers for management and economics journals; · Interest in platforms, digitization, antitrust, network effects and/or strategy. Basic Qualifications · A Ph.D. in
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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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recordings, behavioral training, and visual experimentation, while also developing and testing deep neural network models of visual representation. In short: experiments first, models second. Current and
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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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data across multi-institutional research networks, with a focus on the analytical and computational challenges arising in precision medicine, mental health, and biomedical informatics. The postdoctoral
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of complex systems, networks, and large-scale data Machine learning, generative AI, NLP, or algorithmic decision systems Ideal applicants will have a strong background in operations research, statistics
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such as: Causal inference and the design and analysis of experiments Reinforcement learning and sequential decision-making Analysis of complex systems, networks, and large-scale data Machine learning
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units in neural networks, which drive both artificial and natural intelligence. Current projects span a wide range of topics in deep learning theory and theoretical neuroscience. For more information and
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have expertise in one or more of the following areas: Sustainable building systems or materials science Power system modeling, control systems, or HVAC alternatives IoT and sensor networks in the built