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. The Accelerate Programme for Scientific Discovery (https://science.ai.cam.ac.uk/ ) is a high-profile University initiative promoting the use of machine learning to tackle major scientific challenges. Accelerate
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University of Cambridge About us Contact us Job Opportunities Jobs Applying for a job My applications Right to work What we can offer Living in Cambridge Temporary work Work experience Volunteering Page not found This page cannot be displayed. If you are returning to a previously accessed job...
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Humanities, the Humanities and Social Sciences and Non-School Institutions. As part of an established team, the post-holder will provide proactive research support across to drive high quality funding
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support to one of the research groups within the Computational and Biological Learning Lab of the Information Engineering Division. Educated to HND/HNC level or equivalent level of experience, you will be
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We seek an energetic and enthusiastic individual to act as Group Administrator to the Computational and Biological Learning Group (CBL). CBL is housed within the Information Engineering Division
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Clinical Research Associate to join a state-of-the-art translational research programme headed by Professor Rebecca Fitzgerald and Dr Massimiliano di Pietro, focusing on novel endoscopic and non-endoscopic
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Salary: circa £30,720 per annum, depending on skills and experience (2025/26 pay award pending) Hours: 37.5 hours per week (exclusive of meal breaks) Contract Type: Permanent, subject to six months’ probation Selwyn College, with a reputation for friendliness and good food, is recruiting for a...
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will be addressed using a series of behavioural and electro-physiological experiments with Cochlear Implant users, as well as comparing the outcomes with predictions from existing computational models
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We are seeking an enthusiastic and independent Research Associate to join our growing research in the Department of Chemical Engineering and Biotechnology at the University of Cambridge. The role
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, test automation, and CI. Services are deployed to cloud infrastructure in Docker containers. Our technology stack is: AWS, GCP, Terraform, Ansible, Docker, Python, Django, React, Material UI and