PhD Studentship: Optimising Revision Hip Arthroplasty Planning

Employer: UCL - Department of Mechanical Engineering

Qualification Type: PhD

Location: London

Funding for: UK Students, EU Students, International Students

Hours: Full Time

Lead Supervisor: Dr Anna Di Laura

Project Start Date: 01 October 2025 or soon after

Project Duration: 4 years (full-time)

Studentship Funding: 4 years of tuition fees (Home rate). International students will receive a UCL award to cover the home/international fee difference. Maintenance stipend (currently at least £22,780 per year, and rises each year)

Background: Revision hip arthroplasty is a complex procedure required when primary replacements fail due to loosening, wear, infection, or fracture. Success is often challenged by altered anatomy and bone loss, making planning and decision-making difficult. While CT imaging is essential for assessing bone morphology, implant position, and peri-implant osteolysis, image quality is frequently degraded by metal artefacts, limiting diagnostic accuracy and compromising surgical outcomes. Emerging tools, such as metal artefact reduction (MAR) algorithms, AI-based segmentation, and automated 3D anatomical modelling, promise clearer, more reliable imaging. Integrated effectively into clinical workflows, these advances have the potential to produce clearer, more reliable visualisations of bone and implant structures, thereby enhancing the accuracy of pre-operative planning and enabling more precise, patient-specific surgical strategies.

Aim: The principal aim of this research is to develop, validate, and implement advanced CT image-processing techniques designed to optimise pre-operative planning in revision hip arthroplasty. A key strength of this PhD is its strong clinical integration. The project will be undertaken in close collaboration with clinicians at the Royal National Orthopaedic Hospital, ensuring that the research is directly informed by clinical challenges and patient needs. This clinical input will guide the development of image-processing tools, support validation in real-world surgical contexts, maximise translational impact. The student will also benefit from engineering expertise at Synopsys/Ansys, and from training in high-impact research at UCL.

Summary: This body of research is an exciting collaboration between UCL Mechanical Engineering, the Royal National Orthopaedic Hospital, and Synopsys/Ansys, aimed at improving the planning and delivery of redo hip replacements to make a real difference in the lives of patients. By combining clinical expertise, cutting-edge engineering, and advanced simulation tools, this project offers a unique opportunity for PhD students to contribute to transformative research with direct patient impact.

Person Specification: Applicants must have a UK-equivalent first degree in mechanical engineering, software engineering, or a related discipline. A passion for simulation/mathematical modelling, experimental evaluation and data analysis. Excellent organisational, interpersonal and communication skills, along with a stated interest in interdisciplinary research and creativity, are essential. Experience in computer programming and design would be essential. Experience in one or more of the following: Image analysis, Matlab and Python programming, Machine Learning. Fluency and clarity in spoken English as well as good written English in accordance with UCL English requirements.

How to Apply: Step 1: Submit a PhD application via the UCL website. Step 2: Email the lead project supervisor, Dr Anna Di Laura at anna.laura.14@ucl.ac.uk and enclose the following documents: A one-page research proposal, A one-page statement outlining your motivation for the project, A two-page CV, A copy of your university transcripts.