Multiscale Imaging and Mechanics of Osteoarthritis

About the Project

Osteoarthritis (OA) is a progressive, age-related musculoskeletal disease and a leading cause of pain and disability worldwide, affecting approximately 7% of the global population. Despite its high prevalence, the mechanistic drivers of OA initiation and progression remain poorly understood, particularly in the early stages of disease. This project will be the first to couple the world’s highest resolution imaging (static ex vivo) of human knees with dynamic imaging of large animal models of OA. Both static and dynamics imaging experiments will be performed at the European Synchrotron in Grenoble, France, using the state-of-the-art Hierarchical Phase-Contrast Tomography (HiP-CT) technology.

The human knee scans will provide hard and soft tissue morphology, whilst the animal models will be used to characterise how joint structure governs dynamic mechanical function during disease onset and progression. 3D datasets of joints under controlled ex vivo loading will be acquired and full-field strain quantified using Digital Volume Correlation (DVC), alongside detailed mapping of joint micro-architecture. The PhD is part of a larger collaborative project and will generate the first integrated datasets linking microstructural features of the osteochondral interface to their corresponding mechanical strain environments in intact animal joints.

These results will be integrated into machine learning and computational models to identify predictive relationships between joint architecture and mechanical behaviour across defined disease stages. You will help establish a scalable framework for translating mechanistic insights derived from large animal models into broader principals of joint degeneration. These data will further provide critical insight into how structural heterogeneity drives abnormal load distribution and focal stress concentrations associated with OA susceptibility.

This project is a collaboration between University College London (UCL), the Royal Veterinary College (RVC; world-leading expertise in OA animal models), and the European Synchrotron Radiation Facility (ESRF), where HiP-CT imaging will be performed. The student will work within a highly interdisciplinary team, including experts in imaging (Prof. Peter Lee), computational modelling (Profs. Ryo Torii & Lee), and osteoarthritis biology (Prof. Andrew Pitsillides), alongside dedicated input from Dr Sharma (biological imaging and quantitative morphology) and Dr Chen (computational modelling).

The successful candidate will be part of a team (MXILab) investigating how joint micro-architecture drives mechanical dysfunction in knee osteoarthritis using ex vivo dynamic large animal dynamic models and static human. Intact animal joints will be imaged under controlled ex vivo loading using ultra-high resolution synchrotron tomography (HiP-CT), enabling three-dimensional visualisation from organ to cellular scales. Digital Volume Correlation will be applied to quantify full-field displacements and strains within the osteochondral unit, allowing direct linkage between subchondral bone and cartilage structure and their mechanical behaviour. The student will process and analyse large volumetric datasets, including image reconstruction, registration, and segmentation, to extract quantitative measures of joint morphology. These data will be integrated with computational modelling approaches to identify how structural heterogeneity drives abnormal load distribution and focal stress concentrations during disease progression.

Person specification

Applicants should hold, or be expected to achieve, a first-class undergraduate degree (or equivalent) in a relevant discipline (e.g. biomechanical engineering, mechanical engineering, biophysics, or related fields).

A strong foundation in biomechanics, along with solid design and engineering skills, is essential.

Experience or interest in experimental rig development, biomedical imaging, and coding is highly desirable.

Candidates should demonstrate excellent organisational, interpersonal, and communication skills, and a clear interest in interdisciplinary research.

Eligibility

Please note that the available funding supports tuition fees at the Home/UK rate. Students who are eligible to pay fees at the UK rate are welcome to apply. Please refer to our website for further information about Home tuition fee eligibility.

International students who are eligible to pay tuition fees at the Overseas rate will also be considered, however the tuition fees covered by the studentship will be limited to the Home/UK level. International students will be required to find additional funding for the remaining Overseas tuition fees.

Applicants whose first language is not English are required to meet UCL’s English language entry requirements.

Please refer to this webpage for full eligibility criteria: Mechanical Engineering MPhil/PhD

How to apply

Eligible applicants should first contact Prof. Peter D. Lee (peter.lee@ucl.ac.uk). Please enclose the following documents:

• A one-page statement outlining suitability for the project
• A two-page CV (including contact details of two referees)

After discussing the project with Professor Lee, eligible applicants should also submit a formal PhD application via the UCL website.

The supervisory team will arrange interviews for short-listed candidates.

Funding Notes

Application deadline: Ongoing

Project start date: 01 October 2026

Project duration: 4 years (full-time)

Studentship funding provided: Home tuition fees (currently £6,400/year) and maintenance stipend (currently £23,805/year) for 3.5 years