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systems, autonomous vehicle control, robotics, numerical simulation and the ability to develop algorithms in research environments will be an advantage. - PROFESSIONAL EXPERIENCE. 50 % Prior experience
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Overview We are seeking an experienced researcher to lead the development of decentralised swarm mapping and localisation algorithms for underground pipe operations as part of an international
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advanced digital technologies, with research spanning fundamental methodological development through to real-world application and evaluation. Key areas include AI, data science, trustworthy and explainable
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. Work will emphasize the development and analysis of advanced methods in areas such as sparse signal recovery, compressed sensing, and statistical estimation, with a particular focus on their role in
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algorithms that enable artificial agents to acquire skills through interaction (feedback) with humans. The objectives include: the development of reinforcement learning algorithms; possibly the study of
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Department BSD SUR - OHNS: Thirty Million Words - R&D About the Department The TMW Center for Early Learning + Public Health at the University of Chicago develops, tests, and implements evidence
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relationships between them. Possible directions for the project include (the final scope will be developed together with the candidate, and it is not necessary to cover all topics): Group fairness: developing and
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the interface between the classical and quantum worlds. You will design QEC codes suited to realistic hardware, develop the decoding algorithms that make them practical, and map the trade-offs between reliability
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Developer- AI Literacy and Policy Fundamentals: Understanding and Mitigating Algorithmic Bias  Location: Remote (U.S. based only) Division: Rabb School of Continuing Studies in collaboration with the Heller
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reliable comparative database. Finally, the candidate must be able to develop and apply classification algorithms for discriminating between asbestos-cement roofs. Where to apply Website https://xup