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architectures that combine knowledge-grounded reasoning with flexible machine learning Tools that reduce manual burden while preserving traceability and clinical interpretability This position offers the
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architectures that combine knowledge-grounded reasoning with flexible machine learning Tools that reduce manual burden while preserving traceability and clinical interpretability This position offers the
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Knowledge Graphs for Defence and National Security AI) funded by The Turing Grand Challenge on Defence and National Security: https://ernestojimenezruiz.github.io/projects/guard/ . The postdoctoral
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Knowledge Graphs for Defence and National Security AI) funded by The Turing Grand Challenge on Defence and National Security: https://ernestojimenezruiz.github.io/projects/guard/ . The postdoctoral
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expertise in generative AI and natural language processing, particularly in training and fine-tuning large LLMs and VLMs, as well as applying AI inference and spatial reasoning to address critical
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be involved in other collaborative research projects between Coley’s Conceptual Organization, Reasoning, and Education Laboratory (CORE Lab) and Helmuth’s Marine Ecological Forecasting, Ecophysiology
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Contact(s) Please note: Job applications must be submitted directly online only at: ( https://jobs.uri.edu ) Contact Phone/Extension Contact Email Physical Demands Campus Location Kingston Grant Funded Yes
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and Artificial Intelligence (RAI) ( https://www.fieldrobotics.eu/ ) based at Department of Computer Science, Electrical and Space Engineering as part of the national research program WASP. Wallenberg
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 22 hours ago
ideas and perspectives, foster a stimulating research environment and advance knowledge within their fields. Postdocs are crucial members of our scientific research workforce, contributors to our
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The position We are seeking to recruit a postdoctoral researcher to work on understanding the mechanisms of AI reasoning. Their core duty will be to advance our understanding of how LLMs acquire