Research Associate position in computational diffusion MRI of the placenta

The Centre for Medical Image Computing (CMIC: and Dept. Computer Science (UCL-CS: at University College London (UCL:, in collaboration with the Perinatal Imaging Unit at St Thomas’ Hospital, London, UK, is offering new post-doctoral research positions to work on quantitative diffusion MRI of the human placenta.

The new post is within CMIC’s Microstructure Imaging Group and is funded by the US National Institutes of Health (NIH) as part of their Human Placenta Project initiative. The project will develop models linking the MR signal to tissue microstructure with the aim of estimating alterations to the fine structure of placental tissue following successful similar lines of work in cancer and neuroimaging that led to popular techniques such as VERDICT (Panagiotaki Cancer Research 2014) and NODDI (Zhang NeuroImage 2012). The ultimate aim is to provides early signals of pregnancy disruption that offer the specificity to guide accurate and personalised choice of treatment or intervention.

UCL is among the top-ten world-wide research institutions, is the most highly-cited European institute by health researcher, has particular strengths in Biomedicine and Engineering and is in the heart of central London. CMIC combines methodological researchers from the Departments of CS and Medical Physics & Bioengineering with biomedical and clinical groups in UCL’s Faculty of Biomedicine. The interface of engineering with medicine, where CMIC specializes, is a unique and exciting place to do cutting-edge research.

Applicants must have, or expect to obtain, a PhD in a relevant discipline. Strong maths, statistics, and programming skills are essential, as well as a good publication record in relevant journals. Previous experience with computational and statistical modelling, medical imaging (especially MRI), medical and healthcare applications, and MATLAB are all advantageous. The appointment will be made on the Research Associate salary scale ( at grade 7, depending on experience, and will be funded for 2 years.

Further details and information on how to apply can be found here.

Informal enquiries to Prof. Daniel Alexander for further information are welcome.

The closing date for applications is 24th Jan 2016.