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the sources of outbreaks, and c) identify potential drug targets for prophylactic or therapeutic purposes to prevent colonization or limit the spread of these infectious agents. The project seeks to map how
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health records. Medical Reasoning and Grounding: Developing advanced post-training and alignment techniques (RLHF, DPO, GRPO) to ensure foundation health models reason accurately and safely. Agentic
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, efficiency enhancements result in rebound effects due to feedback between enhanced efficiency and food system economics. The successful candidate will collaborate in a multi-disciplinary, international team
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and neural activity. In particular, Postdoctoral AI Researchers may help develop brain foundation models that predict patterns of neural activity from large-scale, multi-regional recordings. Areas
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team and contribute to IDEAS (Intelligent Data Exploration Assistant for Science), a multi-year research effort focused on developing AI-powered visualization systems that enable interactive, human-in
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PostDocs on the development of cutting-edge AI-ready/agentic infrastructure for data and model discovery, model metadata extraction, and scholarly intelligence. The project will explore conceptual frameworks
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for genomics (e.g., generative models, transformers, agentic workflows) and/or statistical learning (e.g., network & spatiotemporal modeling, functional/longitudinal data, time-series). Analyze single-cell
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-level computational model of the human cell. The program is led by Jan Ellenberg, Director of SciLifeLab and Mathias Ulhen, Director of the Human Protein Atlas, together with a collaborative, multi
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and multi-agent systems for conservation genomics; perform feature engineering using chromosome-level genome assemblies. 15% Writing: Contribute to scientific manuscripts, progress reports, and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 12 days ago
contribute to the development of next-generation AI software within the ACM Lab that leverages LLMs, multi-agent reasoning, and advanced machine-learning techniques to enable rapid, scalable analysis of large