81 parallel-computing-numerical-methods positions at UNIVERSITY OF SOUTHAMPTON in United Kingdom
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Part-time (0.6fte+) or Full-Time. The University of Southampton invites applications for a Lecturer (A or B, level 4 or 5) from candidates with interests in AI, quantitative research methods
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The University of Southampton is seeking to make the appointment to the role of Senior CAFM Manager. The University of Southampton is a leading research-intensive University, a founding member of the prestigious Russell Group, and one of the top 100 universities worldwide. We deliver excellent...
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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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). Adhering to agreed service principles and maintaining security and compliance is also a crucial part of the role. A proven track record in delivering onsite support including within the computing labs is key
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address this, you will adopt a novel "top-down" strategy, directly opposed to the current materials discovery methods, to accelerate materials development for creep-fatigue environments. Specifically, you
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complex health and social care challenges, particularly in the management of long-term conditions. We combine AI and traditional epidemiology with qualitative methods to develop impactful, real-world