716 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Univ" "Univ" positions at Harvard University
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an individual with a PhD to conduct research in the area of biomedical informatics, multi-omic integratoin analytics and machine learning. In this role you will produce highly impactful biomedical informatics
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Science Statistics / Biostatistics Applied Mathematics Data Science Demonstrated expertise in modern machine learning, including at least one of the following: Deep learning (e.g., transformers, sequence models
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diverse, inclusive community dedicated to alleviating suffering and improving health and well-being for all through excellence in teaching and learning, discovery and scholarship, and service and leadership
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potwashing/dish area, walls, floors and counters. Fills, empties, operates and performs regular maintenance on pot washing machine or manually washes pots as required. Monitors and records temperatures and
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potwashing/dish area, walls, floors and counters. Fills, empties, operates and performs regular maintenance on pot washing machine or manually washes pots as required. Monitors and records temperatures and
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to have a strong background in the foundations of machine learning. Special Instructions Required application documents include a cover letter, CV, a statement of research interests, and up to three
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of public benefits, and generative AI-based tools. Leverage recent breakthroughs in machine learning and natural language processing to build, test, and deploy advanced algorithmic tools that underpin
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customer service orientation. Strong computer skills (Word, Excel, PowerPoint, Outlook, and internet) and willingness/ability to learn and adapt to new software and technologies. Experience with or knowledge
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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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generative AI-based tools. Leverage recent breakthroughs in machine learning and natural language processing to build, test, and deploy advanced algorithmic tools that underpin rigorous empirical research in