16 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" uni jobs at The University of Southampton
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specification, as well as an indication of the reasons for your interest in this opportunity. Completed applications should be uploaded at https://plusportal.perrettlaver.com/VacancyDetail/f489f8ce-0fd8-33e1-0ca9
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. Working as part of SoC labs (https://soclabs.org/), you will design, develop and deliver workshops, lectures and online learning content in areas including digital electronic design, system‑on‑chip (SoC
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. There are opportunities to teach on courses run at the University and with partner charities and organisations, as well as be involved in audit and service development within USAIS. You will also have a key role in the
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education taking place in the Faculty of Medicine can be found on the Faculty of Medicine website at https://www.southampton.ac.uk/about/faculties-schools-departments/faculty-of-medicine This teaching fellow
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the Digital Services application support team who are responsible for the digital services that underpin the work of NIHRCC and also offer support to the School. Further information can be found at: https
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place in the Faculty of Medicine can be found on the Faculty of Medicine website at https://www.southampton.ac.uk/study/subjects/medicine . You will be involved in module leadership, teaching, curriculum
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with our four research centres (https://www.southampton.ac.uk/research/areas/psychology ). We particularly welcome applications from candidates whose research can contribute to one or more of our cross
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globally recognised degree without leaving the country. Job Purpose The role holder’s contribution will be central to delivery and support of teaching, learning and assessment, across Business for the
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globally recognised degree without leaving the country. Job Purpose The role holder’s contribution will be central to delivery and support of teaching, learning and assessment, across Business for the
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that intersects with emerging fields such as digital tribology, machine learning for predictive wear modelling, sustainable materials, or tribological challenges in clean energy systems and advanced manufacturing