Deadline: Applications will be accepted at any time until the position is filled.

Disabilities due to musculoskeletal disorders have increased by nearly 50% over the last 20 years and affect millions of people. Osteoarthritis is the fastest increasing major health problem worldwide and every year, more than 300,000 people suffer from an osteoporosis-related fracture in the UK only. There is intense research to try and study the origin of these musculoskeletal disorders although, critically, until recently the hallmarks of these bone-related diseases could not be studied in 3D at a cellular level. Therefore, we are currently developing a framework for 3D bone imaging at the cell level.

Within this PhD project we will address the persisting controversy on how mechanical loading is magnified and transferred to bone cells, which are critically involved in the pathogenesis of metabolic bone diseases such as osteoporosis or osteoarthritis. To this end, the PhD candidate will derive quantitative hallmarks of bone at the cell level in health and disease from osteoarthritic and osteoporotic patients and from rodent cohorts used in nutritional studies. The PhD candidate will develop realistic computational modelling and approaches to investigate mechanotransduction at the cell level for the different bone health conditions. This will allow identifying cellular targets for diagnosing bone diseases and assessing treatment success in future pre-clinical and clinical studies.

This PhD offers a unique interdisciplinary life sciences programme of work based at a world-class research centre with shared support from the Faculties of Engineering and the Environment and Medicine at the University of Southampton (UoS). The PhD candidate will work closely with partners at the Southampton General Hospital and the X-Ray Imaging Centre μ-VIS at UoS, while benefitting from the exceptional opportunity to gain expertise in cutting-edge bioimaging technologies and computational modelling methods applied to relevant health questions in our society.

The ideal candidate will have biomedical imaging experience and a good knowledge of computational modelling approaches. In general, the candidate must have a strong background in engineering sciences.

If you wish to discuss any details of the project informally, please contact Philipp Schneider, Bioengineering Science Research Group, Email: p.schneider<στο>soton.ac.uk, Tel: +44 (0) 23 8059 4640.