25 unconventional-computing Fellowship positions at UNIVERSITY OF SOUTHAMPTON in United Kingdom
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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, faster, longer? Future of Healthful Work – a large scale interdisciplinary program we’re leading asks the question “what if work were healthful from the outset, rather than being something from which we
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delivery of our innovative NxtGen Researcher Programme and help establish the NxtGen Researcher Academy. This multi-disciplinary position focuses on engaging young people in health research, combining
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Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search
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Search over Personal Repositories - Secure and Sovereign”). The post is based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating
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We are seeking a highly motivated post-doctoral researcher of high calibre to join our research program in the area of integrated silicon photonics. The position is funded by the EPSRC (Engineering
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The University of Southampton are seeking to appoint a fixed term research fellow to facilitate and deliver a programme of research on a Faraday Institution funded project: SL2FBat - Sustainable Low
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and innovation (R&I) ecosystem. This is a unique opportunity to establish or expand your research programme in the UK, collaborate with world-class researchers, and contribute to national and global
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the laboratory of Professors Ward and Ober. Their interdisciplinary research program is dedicated to the development of novel antibody-based therapeutics that has led to several therapeutics that are currently in
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental