19 cloud-computing-"https:" "https:" "https:" "https:" "https:" "https:" Postdoctoral positions at King's College London
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(https://doi.org/10.1242/jcs.180703) and Prof. Philippa Francis-West (Mao et al. Nature Comms. 2016 (https://doi: 10.1038/ncomms11469 and Prof. Philippa Francis-West (Mao et al. Nature Comms. 2016 (https
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wireless communications for three decades. For further information, please see here: https://www.kcl.ac.uk/research/ctr About the role: 5G networks are a key enabler for the economy and society’s growing
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About us A post-doctoral research associate position is available at the Photonics & Nanotechnology group, Physics Department, King’s College London, funded by the EPSRC Programme Grant Next
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’ Hospital in central London in the School of Biomedical Engineering & Imaging Sciences at King’s College London: https://www.kcl.ac.uk/bmeis . There is an unmatched infrastructure in place to support the
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including grade 7. Visit the [Centre for Research Staff Development](https: //www.kcl.ac.uk/research/research-environment/professional-development/centre-for-research-staff-development) for more
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the use of computing servers Desirable Criteria Experience fine-tuning large language models (e.g., BERT, BioGPT, MedPaLM) for clinical NLP tasks. Experience with cloud or distributed computing environments
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: The successful candidate will join the Distributed AI (DAI) group in the Department of Informatics, King’s College London. They will carry out research in neuro-symbolic AI, with a focus on using generative and
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provides high-quality contributions to academic debates. You will work closely with Prof. Ben Geiger and Prof. Karen Glaser as part of the Centre’s ‘Work, Welfare Reform and Mental Health’ programme. This
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the Department of Informatics, part of the Faculty of Natural, Mathematical & Engineering Sciences (NMES). The department is internationally recognised for its contributions to robotics, AI, and human-centred
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Hopkins University (USA). About the role The PDRA will lead the development of new computational and mathematical models to quantify and predict infectious disease risk, particularly for identifying high