We are seeking to appoint a Postdoctoral Researcher in Image Analysis who will based at the Big Data Institute and be part of the Oxford analysis team to apply and develop state of the art statistical machine learning algorithms for processing longitudinal MRI images in the Oxford-Novartis Collaboration for AI in Medicine. The primary focus will be optimising and applying existing lesion segmentation tools followed by developing AI tools for MRI lesion segmentation and brain atrophy quantification in longitudinal settings.
Under the line management of Professor Chris Holmes and direction of Professor Thomas Nichols, this position will involve various aspects of statistics and machine learning in biostatistics to integrate the data provided by Novartis in order to provide a greater biological understanding of inflammatory and autoimmune diseases and how that underlies prediction of outcome. It includes provision of design and analysis as well as development of novel statistical approaches to solve problems specific to the Oxford-Novartis Collaboration. Whilst you will be prominently based the Big Data Institute, you will also be expected to spend time at the Department of Statistics as well.
Your responsibilities and duties will include, to adapt existing and develop new tools for lesion segmentation and atrophy quantification as well as conduct comprehensive and systematic literature and database searches. In addition you will manage your own academic research and administrative activities and develop ideas for generating research income as well as and present detailed research proposals to senior researchers. You will also contribute ideas for new research projects and collaborate in the preparation of research publications.
You will hold or be close to completion of a relevant PhD/DPhil in statistics, computer science, engineering or related discipline 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.
The closing date for this post will be 12.00 noon on Wednesday 26 February 2020.
Contact: Genevieve Moffa (01865 612892)