Fully-funded PhD in AI-driven Diagnostics for Musculoskeletal Soft Tissue Injuries at Queen's University Belfast
Queen's University Belfast School of Pharmacy is offering a fully-funded PhD opportunity focused on developing AI-driven diagnostics for musculoskeletal soft tissue injuries (MSTIs). The project aims to create a fingerprint signature for MSTIs by investigating the role of collagen and keratin as biomarkers, utilizing non-invasive nail samples and advanced protein analysis techniques. The research will explore how mutations in chaperone enzymes affect protein folding, using Raman spectroscopy and genomic profiling to build a comprehensive database and AI platform for diagnostic purposes.
Students will receive interdisciplinary training in cloning, synthesis, and purification of recombinant proteins, in-depth Raman analysis, and programming skills in R and Python. The program includes industry placements with Momentum 1.0 (focused on LLM platforms and secure environments) and Crescent Bone Health (CBH), where students will analyze nail samples and learn about MATLAB and industrial QMS systems. Genomic profiling and DNA extraction from nails for Collagen 1 mutations are integral parts of the project.
The PhD is designed to blend scientific innovation with industry-focused training, producing graduates skilled in technical innovation and commercial strategy, highly attractive to pharmaceutical, biotechnology, and medical technology sectors. Strategic partnerships with industry and patient stakeholders ensure the research aligns with real-world needs, and a human-centred translational toolkit will help students understand user acceptance and adoption of new biotechnologies.
Funding covers tuition fees, stipend, and research costs for UK and ROI students, provided through a Collaborative Studentship Award with Crescent Bone Health. The School of Pharmacy at Queen's University Belfast is internationally recognized for research excellence in pharmaceutical sciences, drug delivery, nanomedicine, biomaterials, infection and antimicrobial resistance, and healthcare delivery. Students benefit from world-class facilities, a dedicated Graduate School, and support from leading academic experts.
Applicants should have a strong academic background in pharmacy, biomedical sciences, biology, or related fields, with interest or experience in AI, machine learning, genomics, and protein analysis. Critical thinking, organizational skills, and willingness to participate in industry placements are expected. The application deadline is 16 January 2026, with the program starting on 1 June 2026.
For more information and to apply, visit
http://go.qub.ac.uk/HMPhD1
or contact Professor Helen McCarthy at
[email protected]
.