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Field
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About the Opportunity About the Institute Do you want to be part of an exciting new Institute focused on combining human and machine intelligence into working AI solutions? We are launching a
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Informatics, Health Data Science, Biostatistics, or a closely related area. Strong ML/deep learning foundation plus expertise in at least one of: multimodal learning, time-series modeling, or NLP. Demonstrated
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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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at finale.seas.harvard.edu and our group’s webpage https://dtak.github.io/ We work on probabilistic models, reinforcement learning, and interpretability + human factors. Basic Qualifications Candidates are required to have
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following use cases: • The construction of a machine learning pipeline that allows the conversion of Course Unit Sheets (CUS) into a data structure based on the European Learning Model (ELM). • Integration
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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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estimation to begin in Spring/Summer 2026. The successful applicant will develop and implement data-driven tools, underpinned by scientific machine learning and reduced-order modeling, for ocean state
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into the models for calibration (via PEST/PEST++) and for regionalization of results using machine learning algorithms. Field surveys in the Portuguese study areas will be required to maintain and upgrade
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questions and data of CREATE. The successful candidate will conduct advanced methodological and psychometric research. Potential topics include (a) AI, machine learning, and large language models
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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