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Field
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advancing the state of knowledge in their chosen research area. Criteria of the candidate: PhD in: Computer Science, Artificial Intelligence, Data Science or related fields (Computational Physics
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multidisciplinary project led by Paloma Cejas and Henry Long, in collaboration with AITIA, an artificial intelligence and computational biology company. The project focuses on understanding patient responses to
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these areas Your profile Excited to bring biology into the agentic era Broad interest across biological domains is a must PhD in computational biology, computer engineering, computer science, (bio
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Intelligence, Biomedical Ontologies, Biomedical Knowledge Graphs, Computational Biology, Bioinformatics, Biomedical Informatics or a related field. Programming experience in a language such as Python
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degree). Strong background in one or more of the following: Computer Vision Machine Learning Artificial Intelligence Computational Behavioral Science Data Science Biomedical Engineering Computational
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, biomedical data science, artificial intelligence, genetics, imaging, and multi-omics discovery. The fellow will help develop and apply computational approaches to study heart failure mechanisms and
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disease. The Postdoctoral Associate must hold an MD or MD/PhD degree with clinical research experience, or a PhD degree in biomedical engineering, medical physics, computational science, or a related
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experience (minimum £35608 with relevant PhD). Closing Date Friday 09 October 2026 Reference MED802626 About the role We are seeking a highly motivated Research Associate/Fellow to join a
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advanced computational approaches, including radiomics, artificial intelligence, machine learning, image analysis, and longitudinal imaging assessment. · Integrate multimodal imaging data with
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Data Science (CarDS) Laboratory. The group develops clinically grounded artificial-intelligence and data-science methods to derive scalable digital biomarkers from echocardiography, cardiac computed