149 algorithm-phd-"INSAIT---The-Institute-for-Computer-Science" positions at University of Cambridge
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Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country United Kingdom Application Deadline 15 Sep 2025 - 23:59 (Europe/London) Type of Contract Temporary Job Status Full-time Offer
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Two fully-funded 3-year PhD studentships are available in Neuromorphic and Bio-inspired computing at the interface between control engineering, electrical engineering, computational neuroscience
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A PhD studentship is available to work on Logistics automation. The student associate will work in the Intelligent Logistics Group within the Distributed Information and Automation Laboratory (DIAL
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and Technology (CST) at the University of Cambridge. The goal of this PhD programme is to launch one "deceptive by design" project that combines the perspectives of human-computer interaction (HCI) and
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, please send your one-page cover letter and two-page CV to Professor Nathan Crilly [nc266@cam.ac.uk ]. The message header should be "JLR PhD Application". Emails should arrive no later than 1 September 2025
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the Further Information document Further information on the Faculty of History's PhD programme can be found here: https://www.postgraduate.study.cam.ac.uk/courses/directory/hihipdhis and https
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Applications are invited for a PhD studentship on the project EQUATE - a project that investigates how Natural Language Processing (NLP) could be made globally more equitable. This UKRI Frontier
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catalytically active metals to drive chemical reactions with light [3-4]. The specific goals of this PhD project are to 1) understand how plasmonic Mg nanoparticles and their surface oxide layer attract and
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pivotal role in analysing large-scale genomic and clinical data, applying cutting-edge algorithms, and collaborating with renowned experts in the field. At PBCI, we believe in fostering a collaborative and
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the coordination of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real