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treatments. To achieve this, we will develop personalised cardiac models at scale, and update these models over time, using imaging and electrical data collected by collaborators at multiple centres. We
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on autofluorescence (AF) imaging and Raman spectroscopy for detection of metastatic lymph nodes during breast cancer surgery. Engaging with and reporting to Dr Alexey A. Koloydenko (Department of
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potential applications in audio and music processing. Standard neural network training practices largely follow an open-loop paradigm, where the evolving state of the model typically does not influence
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physiologically relevant models will provide crucial platforms to mimic disease pathology, and better understand and treat tendinopathy. The project will generate tendon-chips using in-house commercially available
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cancer in Barrett’s esophagus. Experience in analysing large datasets in R is essential but will also involve the use image analysis software such as Qpath. About You We seek an ambitious and self
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et al, Leukemia 2018; Poynton et al, Blood Adv 2023; Coulter et al, J Mol Diagn 2024). The wet lab/computational biology postdoc will lead a project investigating residual follicular lymphoma cell
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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well as qualitative approaches including semi-structured interviews with women, families, and clinicians. These interviews will inform the design process and deepen understanding of the everyday contexts and
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defending the cultural value of knowledge for its own sake. You will also possess computational expertise in data mining and / or analysis, ideally including language processing, and be able to work with an
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and inclusive community is embedded in our appointments processes. Reasonable adjustments will be made at each stage of the recruitment process for any candidate with a disability. We are open to