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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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of cancer research and it 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
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imagination for atomistic structure and dynamics; an interest in fundamental science with real-world applications; and both the initiative to work independently and the skill to collaborate in a
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materials. Practical experience in fabricating 2D materials and a deep understanding of their structure-property relationships are highly desirable. You should also have expertise in advanced characterisation
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in the laboratory, in patients and in populations. BCI is internationally renowned in many areas of cancer research and it combines ground-breaking basic research with the expertise of clinicians and
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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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-edge machine learning techniques will be used, including Large Language Models (LLMs). About Queen Mary At Queen Mary University of London, we believe that a diversity of ideas helps us achieve the
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About the Role Applications are invited for one Postdoctoral Research Associate with expertise in structural biology to join the research group of Aravindan Ilangovan at Queen Mary University
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of those with and at risk of cancer through innovative research in the laboratory, in patients and in populations. BCI is internationally renowned in many areas of cancer research, and it combines ground
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status, race, religion or belief, sexual orientation, or trans status or history. More information on our structures and initiatives around EDI, including information on staff diversity networks, can be