575 cloud-computing-"https:" "https:" "https:" "https:" "https:" "St" "St" Fellowship positions in United Kingdom
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biggest challenges. We are seeking a Research Fellow in Liquid Metal Artificial Enzymes to join the School of Electronics and Computer Science (ECS) at the University of Southampton. The successful
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-intensive Universities? As a Research Fellow in Computational Climate Politics you will work on the UKRI FLF project “Understanding normative change to address the climate emergency ”. This is a 4+3 grant
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biggest challenges. We are seeking a Research Fellow in Liquid Metal Artificial Enzymes to join the School of Electronics and Computer Science (ECS) at the University of Southampton. The successful
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analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during
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programme, Deep Molecular Phenotyping of Metastatic Breast Cancer. This ambitious, interdisciplinary project aims to generate an integrated, multi-omic understanding of secondary (metastatic) breast cancer
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supervise a Graduate Engineer, coordinate external contractors and specialist consultants, manage laboratory safety implementation, and ensure delivery of the programme to agreed technical objectives, budget
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discussion about the position, please contact Dr Yoshishige Tsuchiya (yt2@ecs.soton.ac.uk ). Equality, diversity and Inclusion is central to the ethos in the School of Electronics and Computer Science. We
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detector approximately eight times larger than that used in T2K. Hyper-Kamiokande will undertake a rich programme of physics, including studies of CP-violation, neutrino oscillations, proton decay
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of Electronics and Computer Science. We are commited to improving equality for women in science and have been successful in achieving an Athena SWAN silver award in 2025. We give full consideration to applicants
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working with Johnson Matthey, but aligned with the EPSRC funded Programme Grant “Dialling up performance for on demand manufacturing” (EPSRC reference: EP/W017032/1). Our vision is to create a toolkit and