The University of Oxford is a complex and stimulating organisation, which enjoys an international reputation as a world-class centre of excellence in research and teaching. It employs over 10,000 staff and has a student population of over 21,000. The University, including the colleges and Oxford University Press, is the largest employer in Oxford and the second largest in Oxfordshire, injecting £750 million annually into the regional economy.
Most staff are directly appointed and managed by one of the University’s 130 departments or other units within a highly devolved operational structure - this includes 5,900 ‘academic-related’ staff (postgraduate research, computing, senior library, and administrative staff) and 2,820 ‘support’ staff (including clerical, library, technical, and manual staff).
There are also over 1,600 academic staff (professors, readers, lecturers), whose appointments are in the main overseen by a combination of broader divisional and local faculty board/departmental structures. Academics are generally all also employed by one of the 38 constituent colleges of the University as well as by the central University itself.
In 2010-11, total University income was £919.6m. Oxford is one of Europe's most innovative and entrepreneurial universities: income from external research grants and contracts. In 2010-11 41% (£376.7m) of total income was derived from external research sponsors, and more than 60 spin-off companies have been created.
Oxford Population Health (Nuffield Department of Population Health) contains world renowned population health research groups and provides an excellent environment for multi-disciplinary research and teaching. Oxford Population Health is a key partner in the Big Data Institute (BDI), contains world-renowned population health research groups and is an excellent environment for multi-disciplinary teaching and research.
As a Researcher working on the Oxford – Novo Nordisk Collaboration, you will conduct genetic discovery analyses using novel microvascular phenotypes derived using machine learning models from multimodal data (including imaging). You will work at the cutting edge of what can be achieved with artificial intelligence and machine learning, and the translation of these findings to lead the way into development of treatments for patients.
To be considered you will hold (or be close to completion of) a PhD in statistical genetics, genetic epidemiology, or a closely related field. You will also have an excellent understanding of common statistical genetics methods, experience of applying genetic discovery methods to real clinical problems and previous experience of first author contribution in leading journals.
The position is full time (part time considered) and fixed-term for 2.5 years. The closing date for application is 12.00 noon on 3rd October 2022.
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