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learning, the topology and geometry of data, or the dynamics of learning. The successful candidate should have, or be expecting soon to receive, a PhD in Mathematics, or related field, with demonstrated
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implementing bioinformatics pipelines from raw data, applying a range of advanced statistical, machine learning, and artificial intelligence (AI) techniques to analyse 'omics and clinical data, and contributing
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from backgrounds, including computational chemistry, bioinformatics, systems biology, physics and machine learning. The project offers a unique opportunity to collaborate closely with experimental
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implementing bioinformatics pipelines from raw data, applying a range of advanced statistical, machine learning, and artificial intelligence (AI) techniques to analyse 'omics and clinical data, and contributing
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innovations in computer vision and computer graphics (segmentation, registration, tracking and visualisation) to enable real-time interaction for surgical planning and decision making. The project will provide
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within the role to pursue an independent research project in the general remit of gene expression and the lab. Candidates with interest or experience in machine learning, artificial intelligence and
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applications to external bodies. We’re looking for a highly motivated scientist with: A PhD in Physics, Chemistry, or Biochemistry. Proven expertise in Raman/IR spectroscopy & machine learning classification
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candidates will have a PhD or equivalent in a relevant discipline and experience in the development of machine/deep learning (ML/DL) methods for engineering and will use this experience in collaboration with
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is aimed at technical innovations in computer vision and computer graphics (segmentation, registration, tracking and visualisation) to enable real-time interaction for surgical planning and decision
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turbine engines. Successful candidates will have a PhD or equivalent in a relevant discipline and experience in the development of machine/deep learning (ML/DL) methods for engineering and will use