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a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience against different interfering systems. Develop, with colleagues, a spectrum
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systems on software defined radio (SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide
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. The successful applicant will use state of the art inference algorithms to design, use and share the findings of epidemiological models that integrate across large and diverse datasets including capture-mark
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for this role. This role will involve developing and applying analysis plans using a variety of advanced methods with the support of project supervisors. The postholder will have completed a PhD in a relevant
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change to delivery of health services. Experience with large datasets and excellent communications skills will be essential for this role. This role will involve developing and applying analysis plans
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responsibilities Research: Contribute to or lead on the statistical aspects of the development of high quality research bids to evaluate the effectiveness of new health technologies, which is recognised both
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institutions, and leading industry partners. The successful candidate will contribute to the delivery of high-impact research projects involving AI algorithm evaluation and image data analysis. You will play a
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bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms Downloading a copy of our Job Description Full
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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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COG-MHEAR is a world-leading cross-disciplinary research programme funded under the EPSRC Transformative Healthcare Technologies 2050 Call. The programme aims to develop truly personalized