707 associate-professor-computer "https:" "https:" "https:" "https:" Fellowship research jobs in United Kingdom
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they may need to further develop (and for which we will provide support). The applicant will also be expected to work side-by-side with staff recruited in computer science and the wider academic team
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conferences in areas of machine learning, computer vision, and Large Language Models and high-impact specialist peer reviewed academic journals. • Ability to conduct interdisciplinary research activities
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relevant to industry demands while working on innovative projects within the university. The research team is seeking a Research Fellow or Research Engineer with strong expertise in Human-Computer
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/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related disciplines. Knowledge of autonomous vehicles or cyber security will be
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on delivering high-quality teaching and diverse, real-world research. We specialise in biosciences, chemistry, computing and technology, as well as engineering, forensic science, mathematics, physics
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Associate on this project, you will be at the heart of an ambitious effort to transform how we quantify the drivers of infectious disease transmission, i.e. the drivers of the effective reproduction number
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develop foundational security theory for agentic and multi-agent AI systems, as part of our research programme in multi-agent security. You will build formal models of security-relevant behaviour in
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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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brain prioritises behaviour when animals face conflicting internal needs and changing environmental demands. This position forms part of the Wellcome Trust Discovery Award programme “Decoding Competition
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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