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a network for developers and users of imaging and analysis tools

We invite applications for one of five positions of a Post-Doctoral Research Associate to work in the newly established EPSRC Centre for Mathematical and Statistical Analysis of Multi-modal Clinical Imaging at the University of Cambridge. The Centre is a collaboration between mathematics, engineering, physics and biomedical scientists and clinicians, and aims to achieve synergies between applied mathematics and statistics through the focus on the analysis of clinical imaging, particularly that arising in neurological, cardiovascular and oncology imaging.

The research activity of the successful candidate will take place within one or more of multidisciplinary projects joint between investigators within the centre. For further information concerning the types of project the centre is likely to undertake and a list of investigators, please visit:

The five PDRAs will form a cohort of researchers in the mathematical and statistical analysis of clinical imaging, with positions available initially for two years and possibly extendible for a further two years (subject to review).

Duties include developing and conducting individual and collaborative research objectives, proposals and projects. The role holder will be expected to plan and manage their own research and administration, with guidance if required, and to assist in the preparation of proposals and applications to external bodies. He or she must be able to communicate material of a technical nature and be able to build internal and external contacts. He or she may be asked to assist in the supervision of student projects, the development of student research skills, provide instruction or plan/deliver seminars relating to the research area.

Applicants must have (or be about to receive) a PhD degree in mathematics or statistics (or closely related discipline). The ideal candidate will be experienced in one or more of the following areas: statistical imaging / statistical shape analysis, functional data analysis, spatial statistics, inverse problems, computational analysis, optimisation, variational methods in image processing. Experience in parallel computing and C programming skills is desirable.

More information available at:

Informal inquiries can be made by contacting Prof. John Aston or Dr Carola-Bibiane Schönlieb by emailing