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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing
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combines ground-breaking basic research with the expertise of clinicians and clinician scientists from the Centre for Experimental Cancer Medicine and the Barts NHS Trust to achieve improvements in cancer
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About the Role Barocaloric solid-state cooling is a promising new technology that has potential to dramatically reduce the carbon cost of cooling and refrigeration. In an EPSRC-funded collaboration
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multidisciplinary team of clinicians, scientists, nurses and support staff, delivering a programme of research relating to traumatic injury, haemostatic resuscitation and optimisation of patient outcomes. The Centre
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and statistical modelling, statistical image analysis and computer vision, chemometrics, biophysics, bioengineering. Preference will be given to candidates with a demonstrated experience in applying
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About the Role We have an opportunity for a Postdoctoral Research Associate in Machine Learning to join PHURI, within the research team of Dr Joseph Taylor working on improving our understanding and management of anemia, a leading causes of morbidity and mortality globally. The postholder will...
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qualification/experience equivalent to PhD level in a relevant subject area (physics, engineering, computing science, etc.). You will need as essential skills a good knowledge of C++ and python, familiarity with
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and self-motivated postdoctoral researcher with a strong background in molecular and cellular biology, as well as computational biology. A track record of effective communication, teamwork and
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About the Role The purpose of this role is to provide qualitative and quantitative research support for a research and impact programme on food reformulation. This role sits within the Research and
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related to gravitational wave astronomy. The primary aim will be the development of advanced approaches for computational Bayesian Inference to measure the properties of Compact Binary Coalescence signals