We are looking to appoint a Postdoctoral Researcher in Machine Learning to apply and develop state of the art statistical machine learning algorithms for processing longitudinal imaging data (i.e. X-rays and Magnetic Resonance Imaging (MRI)) in the Oxford-Novartis Collaboration for AI in Medicine. The successful candidate will be part of the Oxford analysis team that provides biostatistical expertise for Oxford-Novartis Collaboration for AI in Medicine. The analysis team is working alongside with imaging, machine learning experts and clinicians to deliver best practice analyses for the collaboration. Under the line management of Professor Chris Holmes and direction of Professor Thomas Nichols, this position will involve various aspects of medical image analysis and machine learning in medicine to integrate the data provided by Novartis in order to provide a greater medical understanding of inflammatory and autoimmune diseases such as Ankylosing Spondylitis. Whilst you will be predominantly based at the Big Data Institute, you will also be expected to spend time at the Department of Statistics.
Your responsibilities and duties will include, to adapt existing and develop new tools for extraction of imaging features that could inform about progression of spinal diseases e.g. Ankylosing Spondylitis, as well as adapt existing and develop state of the art statistical machine learning methods disease modelling, reviewing and refining methods as appropriate. You will manage your own academic research and administrative activities, contribute ideas for new research projects and develop ideas for generating research income. In addition you will act as a source of information and advice to other members of the group on methodologies or procedures.
You must hold or be close to completion a relevant PhD/DPhil in statistics, computer science, engineering or related discipline, together with relevant experience and possess sufficient specialist knowledge in the discipline to work within established research programmes.
This full time position is fixed-term for 2 years in the first instance, with the possibility of extension.
Further particulars, including details of how to apply, can be obtained from the document below. Applications for this vacancy should be made online and you will be required to upload a CV and supporting statement as part of your application.
Only applications received by 12.00 midday on Thursday 5 March 2020 can be considered.
Contact: Genevieve Moffa (01865 612892)