34 cloud-computing-"https:"-"https:"-"https:"-"St" research jobs at KINGS COLLEGE LONDON
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or pathway inference tools Experience working in high-performance computing or cloud environments Interest in developing novel computational or statistical methods for muscle biology Enthusiasm for open
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interdisciplinary research and teaching at the intersection of the humanities and computational methods. The successful candidate will join the Computational Humanities research group, a vibrant and collaborative
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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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United Kingdom Application Deadline 2 Dec 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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frameworks and pipelines Familiarity with single-cell multi-omic data integration and network or pathway inference tools Experience working in high-performance computing or cloud environments Interest in
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cloud or distributed computing environments. Familiarity with self-supervised and contrastive learning techniques for aligning text and images (e.g., CLIP, SimCLR). Clinical experience, e.g., interaction
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the ability to translate between clinical and technical language while working with radiology informatics teams. A solid understanding of DICOM standards, PACS and RIS environments, GDPR, and image transfer
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) and reproducible research practices Desirable criteria Experience working with generative models or large language models Experience with large scale GPU-based model training and cloud computing
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engineering. Our interdisciplinary research brings together engineers, computer scientists, physicists, and clinicians to develop cutting-edge technologies that transform healthcare. This position is part of a
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. The successful candidate will work within a multidisciplinary team to unravel the metabolic drivers of HCC biology and transplant rejection through cutting-edge spatial multi-omics and computational metabolic