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Kogias as part of his ERC Starting project titled CloudNG (https://cordis.europa.eu/project/id/101220079 ). The post will be based in the Department of Computing at Imperial College London at the South
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researcher for a two-year position within the ADaM project (Autonomous workflows for Data-driven first-principles Modelling). By leveraging agentic Large Language Models (LLMs), the project will develop
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approaches, including advanced live cell imaging and in vitro motility assays. The position is based in Michael Way’s laboratory at the Francis Crick Institute. Click here to read more about the Way lab
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Job Description We are seeking a visionary researcher to lead the development of transformative global water and infrastructure datasets that underpin AI and process-based hydrologic models. You
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, cooperatives, extension agents, etc. Data scheduling, collection, analysis, interpretation, and presentation. Co-supervise PhD and Master students as well as interns Project management including budget
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outcomes under different market design scenarios. The research will combine machine learning, stochastic optimization, and agent-based modelling with behavioural experiments. Case studies from emerging
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the supervision of PhD or Master students. The recruited person will exploit the existing test benches (Beta source and infrared laser) developed for the first EICROC protype (EICROC0, 4x4 channels) to characterize
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controllability • Learning and calibration strategies for uncertainty-aware language model prediction • Knowledge-augmented and neuro-symbolic approaches for language-based reasoning • Evaluation and design of LLM
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background in individual- /agent-based modelling Experience with modelling of animal energetics Strong R and Netlogo skills Good understanding of movement & population ecology Experience in publishing
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
, and Experience - PhD in Computer Science, Computing, Statistics or Data Science, or related disciplines - Demonstrated hands-on experience training, fine-tuning, or adapting LLMs / generative AI models