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apply Overview About the Role We are seeking a part-time Technical Worker to join the School of Engineering and Materials Sciences at Queen Mary University of London. This position is ideal for current
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University of London. The successful candidate will provide day-to-day support with running undergraduate and postgraduate research projects providing expert advice, training and trouble-shooting support. The
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, some knowledge of learning technology and some experience in training or staff development would enhance your application. About Queen Mary At Queen Mary University of London, we believe that a diversity
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technology workforce. About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the previously unthinkable. Throughout our history, we’ve fostered social
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links. We deliver education to over 5,000 students in China, operating a “flying faculty” model. About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas helps us achieve
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Do you have excellent organisational, IT and teamwork skills? Are you keen to support new ways of teaching and learning in higher education? As Birkbeck, University of London, enters its third
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(SEMS), Queen Mary University of London (QMUL). You will be employed to work in the ERC-funded project EndoTheranostics and will be under the supervision of Prof. Kaspar Althoefer. You will be responsible
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computing, AI, biomedical engineering or signal processing) or a higher degree (e.g. MSc) with substantial experience in multimodal machine learning with appropriate track record. Excellent programming skills
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Contract Type: Fixed Term (Available from 1 July 2024 to 31 August 2026) Location: Bloomsbury, London, UK Hours: 35 hours per week / Full time SOAS University of London is the leading Higher
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of Engineering and Material Sciences at Queen Mary University of London. The project is funded by NERC, under the supervision of Dr. Ketao Zhang and Dr. Paul Balcombe. The project will investigate environmental