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Field
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We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data
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-ray Computed Tomography (XCT) has evolved into a significant "big data" challenge, with a single scanner easily generating over 10TB of data annually. The sheer volume of this structured data creates
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large-scale clinical, laboratory, registry, or other health-related data (experience with Nordic registry data is a plus). Familiarity with biomedical ontologies, controlled vocabularies, or coding
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, natural language processing, biomedical language models, or probabilistic modelling. Prior experience with large-scale clinical, laboratory, registry, or other health-related data (experience with Nordic
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or early detection strategies, avoiding the need for palliative medical therapies, would help save more lives. Cancer Research UK funded an observational trial called HUNTER. Clinical data and samples over
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information in unstructured free-text notes. While structured (coded) fields are commonly reused for research, a substantial amount of nuanced and context-rich patient information remains locked in the large
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values rest on credibility, trust and security. By having the courage to think freely and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your
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(bioinformatics). By applying this approach to the large-scale biological and clinical datasets at our disposal, this advance will pave the way for more precise genetic diagnosis and therapies targeting the right
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Health emergencies, mass casualty events and disasters generate large volumes of operational, clinical and organisational data. However, these data are rarely synthesised into structured, analysable
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learning analysis of biomedical data and bioscientific programming for projects on neurological diseases. The candidate should have experience in the analysis of large-scale biomedical data (omics, clinical