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About us The Department of Informatics at King’s College London is looking to appoint a Postdoctoral Research Associate or Fellow to work in the area of technical AI safety. About the role
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
Not Applicable Offer Starting Date 28 Oct 2025 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 17115-LISBOA2030-FEDER-00850400 Is the Job
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About us The Department of Informatics at King’s College London is looking to appoint a Postdoctoral Research Associate or Fellow to work in the area of technical AI safety. About the role
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to migration-related diversity. The position contributes to advancing methodological innovation through the creative and reliable use of machine learning, AI, and other algorithmic techniques in qualitative
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to the development of innovative solutions and algorithms to enhance 5G network capabilities. Work closely with the Principal Investigator (PI), Co-PI, faculty and research team to plan, track, and deliver project
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Research. We are seeking applications from researchers in the broad domain of computational and applied mathematics, including algorithm analysis, artificial intelligence, combinatorial scientific computing
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The ideal candidate will have a PhD in a relevant subject such as statistics, mathematics, physics, operations research, computer science or data science, and have a strong statistics background
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algorithms and techniques and design, implement, test, and maintain software/tools embodying those methods. You will prepare and submit grant proposals to external funding bodies. This position will also
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4 Sep 2025 Job Information Organisation/Company Instituto Pedro Nunes Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees