30 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "CNRS" uni jobs at Manchester Metropolitan University
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optimist who will inspire and engage our people? Now is a hugely exciting time to join Library and Cultural Services. We are embarking on an ambitious plan to reimagine our profile and portfolio, including
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to be part of a major NERC funding program and be part of the SUPERSLUG team involving researchers from the Universities of Plymouth, Exeter and Newcastle. The project seeks to reveal new fundamental
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, including teaching and on programme assessment, of those they are assessing. ABOUT YOU You will have: • Excellent communication and organisational skills • Strong specialist knowledge in Creative Digital
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access to our employee assistance programme Join a supportive, ambitious PA community and make a meaningful contribution to the success of our University. Your organisational skills, attention to detail
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innovative in teaching and we are recognised as the sector leader in Degree Apprenticeships where we deliver the award winning Digital and Technology Solutions programme in collaboration with a wide range of
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wider skills ecosystem. About the role Reporting directly to the Director of Apprenticeships, you will set the vision for business development and lead a multi‑disciplinary team covering new programme
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researchers in an iterative development cycle. You will use your programming skills and Unity experience to integrate AI models that detect and tag emotional meaning from audio and map these to steer real-time
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related discipline Strong programming skills (e.g. Python, JavaScript or C++) Experience working with Generative AI technologies Experience deploying and integrating AI models across different platforms
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ambitious plan for the diverse communities of Manchester and beyond? If the answer is yes, then this opportunity might be for you! We are looking for a vibrant and dynamic individual to join our award-winning
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development cycle. Your AI programming skills will be utilised to train and fine tune two AI models, one able to detect and tag emotional meaning from audio, and one classifying emotion based on the spoken/sung