575 computing "https:" "https:" "https:" "Genentech" Fellowship research jobs in United Kingdom
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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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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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wider research culture of the University. A key component of the role is the opportunity to develop your own programme of research. Applicants are therefore required to submit a research proposal (1,500
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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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the Project PI. ii. Meeting the deliverables by carrying out the computational simulations and experimental studies planned for under the scope of work of the projects within the timeframe to meet the
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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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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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postdoctoral scientist to work on our Blood Cancer UK-funded programme developing next-generation, off-the-shelf immunotherapies for acute myeloid leukaemia (AML). This three-year project will harness cytotoxic
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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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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