26 algorithm-development-"Prof"-"Prof"-"Prof" Fellowship positions at University of Oxford
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be recognised either as an exceptional practice-focused teacher and programme director, or demonstrate a clear capacity to develop rapidly into this role and will have proven capability and a track
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your own research programme. To aid the development of their academic profile, Fellows will be required to contribute up to three hours of teaching per week for the 24 weeks of each academic year to
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understanding of dark energy. Projects may span a broad range of topics, including improving Type Ia supernova modelling and standardization, developing and applying advanced data analysis and statistical methods
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systems in affected regions. In this role, you will contribute to the development of the study protocol and regulatory submissions, support trial implementation, and oversee the management and analysis
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to multidisciplinary team meetings, trial clinics, and service development, particularly in the delivery of advanced therapies. You will hold a PhD/MD with focus on haemato-oncological disorders, a membership of the
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epidemiology, biostatistics and health economics. You will also have a unique opportunity to develop your clinical experience and expertise in the management of adults with rare bone disorders from the clinics
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departments to project manage the development of a postgraduate taught curriculum in biocultural heritage. About you You will be able to demonstrate attention to detail and a high level of accuracy, and to
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from September 2026 or as soon as possible thereafter. Shorter appointments will be considered in exceptional circumstances. The fellowships offer early career researchers the opportunity to develop
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will have overall responsibility for all aspects of the day-to-day running of the CDT with duties including development and delivery of the curriculum and training programme, oversight of the annual
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. The project will define new near miss and severe morbidity definitions allowing us to identify electronically when significant events happen. We will then develop a large multi-centre maternity routine dataset