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Postdoctoral researcher in machine learning and electronic healthcare data – antibiotic resistance, Covid-19 impacts
  • Machine Learning
  • Big Data
  • Deep Learning
University of Oxford
146 days ago

The Oxford University Big Data Institute (BDI) is a new interdisciplinary research centre aiming to develop, evaluate and deploy efficient methods for acquiring and analysing biomedical data at scale and for exploiting the opportunities arising from such studies. The Nuffield Department of Population Health (NDPH), a key partner in the BDI, contains world-renowned population health research groups and is an excellent environment for multi-disciplinary teaching and research.

As Postdoctoral Researcher in machine learning and electronic healthcare data you will have the opportunity to work on a portfolio of projects using routinely collected data from hospitals in Oxfordshire and elsewhere in the UK. You will have the opportunity to contribute to work being undertaken by the research group, including work to predict which patients are at risk of antibiotic resistant infections, in order to guide the antibiotics given to unwell patients before diagnostic tests, as well as work related to the Covid-19 response.

The role will involve developing the most appropriate analysis plans to address specific research questions in new and ongoing studies, conducting detailed analyses accurately and efficiently and developing or tailoring analytical tools and methodologies appropriate to the work, in collaboration with other members of the research team, which includes senior statisticians and infection clinicians. You will also contribute to manuscripts, presentations and other means of disseminating results and attend scientific seminars, meetings and training as appropriate.

To be considered, you will hold, or be close to completion of, a PhD/DPhil in a relevant scientific subject and possess demonstrable experience, ability and practical success in machine learning and statistics, including applying classical machine learning and deep learning methods. You will also have proficiency in the use of programming languages and software libraries relevant to undertaking machine learning and statistical analyses and a keen interest in biomedical science/medicine.

Informal enquiries should be addressed to Dr David Eyre (

The position is full-time (part-time considered) and fixed-term for 1 year.

The closing date for applications is 12.00 noon on 2 September 2020.

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