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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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work. About you Applicants should hold a PhD/DPhil, or be near completion of a PhD/DPhil in structural biology, biochemistry or related area and have gained experience in a wide range of structural
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Machine Learning, Human-Computing Interactions, Social Sciences, and Public Health. Applicants should hold, or be close to completion of, PhD/DPhil with research experience in computer science, statistics
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biotechnology, design, and engineering across Northumbria, Oxford, and Imperial, as well as start-ups and SME collaborators who are already bringing novel materials to market. Applicants should hold a PhD, or be
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will have a PhD in a relevant scientific discipline and sufficient specialist knowledge relevant to the project to be able to make a start on day one – we do not expect everyone to have all the skills
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posters locally and at national and international conferences, as well as participate in MRC grant’s research programme led by Prof Marco Fritzsche. You must hold a relevant PhD/DPhil (or be near completion
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attached to the project. The successful applicant must hold a PhD/DPhil in a relevant subject. They must have peer-reviewed publications using data science approaches, for example, genetic analysis
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system with integrated sensors. You should hold or be near completion of a PhD/DPhil with relevant experience in the field of robotics, biomedical engineering, information engineering, electrical
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protocols. You will work with limited supervision to design and accurately execute experiments to achieve the goals of the project. Applicants should hold, or be close to completion of, PhD/DPhil in Biology
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other members of the group. You will hold a PhD in cancer biology, tissue imaging or a relevant field and will have previous experience in developing and implementing methods for high content imaging