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* together with relevant experience. You will have a strong technical background in machine learning, especially RL and LLMs. An ability to work independently and as part of a collaborative research team is
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We are seeking a full-time Postdoctoral Research Assistant to join Torr Vision Group at the Department of Engineering Science, central Oxford. The post is funded by EPSRC and is fixed-term
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Department of Building Environment and Energy Engineering Research Associate / Research Assistant (Ref. 260303002) [Appointment period: twelve months] Duties The appointee will assist the project
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team at AMOLF, working on fundamental questions on physical self-learning systems as part of the NWO ENW‑M1 project “How do physical learning systems learn?”. The research position is intended to start
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, graphs, photographs, figures, and manuscripts for papers, meetings, and for publication in journals. Prepare slides for presentation at scientific conferences and meetings. Assist with research grant
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, or related field. Strong programming skills and experience with deep learning models, particularly Large Language Models. Evidence of producing high-quality research outputs. Experience contributing to and
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expected to support the coordination and management of collaborative research projects, including task planning, partner interaction, and reporting activities. You will also assist in the co-supervision and
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record of first-author publications (essential) experience in machine learning and AI a collaborative approach to doing science and willingness to help other lab members curiosity and motivation to work
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the leadership of Principal Investigator Dr Andrew Siemion. Listen's interdisciplinary research has synergies with many of the department's research priorities, including exoplanet studies, machine learning
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current BCM postdocs, and learn about research, career development and support resources designed to help you reach your professional goals. Virtual Programming from the Office of Postdoctoral Affairs will