Applications are invited for a fully funded three-year PhD to commence in October 2020.
The PhD will be based in the School of Mechanical and Design Engineering, Faculty of Technology and will be supervised by Dr Gianluca Tozzi, Dr John Chiverton and Professor Gordon Blunn.
This PhD studentship is one of six PhD studentships funded by the University of Portsmouth in the area of biomaterials and bioengineering. These studentships will support the University’s strategic plan engaging with clinicians working in Portsmouth Hospital Trust to solve real-life medical problems. The successful applicants would be part of a cross-faculty research cluster in medical technologies. This programme of research involves several Schools based in the Faculty of Science and Health and the Faculty of Technology. The vision of the cluster is to train a cohort of PhD students who contribute to the academic environment, some of whom would be expected to develop academic careers in this expanding area whilst others would be employed in the growing international medical technologies industry. Training would be enhanced by extended visits to other institutions involved in similar research and by visits to hospitals to meet with clinicians involved in the research projects
The work on this project will involve:
Advances in X-ray computed tomography (XCT) to visualise and quantify morphology in musculoskeletal soft tissues and biomaterials.
In situ XCT mechanical testing and digital volume correlation (DVC) to evaluate full-field strain distribution in soft tissues and biomaterials when incremental physiological loading is applied.
Musculoskeletal disorders (i.e. osteoarthritis – OA and post-traumatic osteoarthritis - PTOA) have a huge impact on society. In particular, those conditions affect soft tissues such as articular cartilage deterioration and ligament/tendon injury, where the need of understanding their morphology and mechanics is of paramount importance to design new biomaterials and treatments. High-resolution X-ray computed tomography (XCT) offers accurate resolution to visualise and quantify morphology in mineralised tissues such as bone. XCT setups are typically limited to bone tissue imaging due to weak absorption of soft tissues (i.e. cartilage, ligaments). Therefore, they are very difficult to image with sufficient contrast. This project will provide fundamental advances in XCT-based imaging of soft tissues such as ligaments, cartilage and 3D printed or electrospun tissue replacements. The project will benefit from state-of-the-art XCT facilities and dedicated software available at the Zeiss Global Centre (ZGC, SMDE, UoP), which will provide unique phase-contrast/retrieval capability and in situ mechanical rigs to image and mechanically evaluate soft materials, without the need of elaborated staining procedures. The project will be strategic in developing imaging technology at the ZGC to retain its national and international reputation in the evaluation of biological tissues and biomaterials (i.e. DVC) for Bioengineering.
General admissions criteria
You’ll need an upper second class honours degree from an internationally recognised university or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency is required at a minimum of IELTS band 6.5 with no component score below 6.0.
Specific candidate requirements
You should be qualified to degree level in Mechanical Engineering, Bioengineering, Materials Science or biomaterial-related area. Experience in imaging technology is desirable but not necessary; however, you should be keen to learn new techniques and analytical methods.
How to Apply
We’d encourage you to contact Dr Gianluca Tozzi ([email protected]
) to discuss your interest before you apply, quoting the project code.
When you are ready to apply, you can use our online application form. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process.
If you want to be considered for this funded PhD opportunity you must quote project code SMDE5070120 when applying.