Research Associate – Musculoskeletal Biomechanics Research Facility (MSKBRF), Cardiff School of Engineering
The Musculoskeletal Biomechanics Research Facility (MSKBRF), Cardiff School of Engineering is leading an EPSRC project in collaboration with Imperial College London. This role offers the opportunity to work with the internationally recognised research teams from the UK, US and Belgium, and industry partners on the development of a Multi‑platform pipeline for engineering human knee joint function (ENGIN KNEE). The project combines advanced computer modelling (in silico), robot‑driven testing of implanted knees (in vitro) and 3‑dimensional X‑ray imaging of moving patients (in vivo) with Machine Learning‑driven analysis to deliver a knee joint analysis pipeline capable of driving surgical innovation beyond 2030.
The work programme, based at Cardiff University and in collaboration with Katholik University Leuven, Belgium, and University of Florida, USA, will develop and validate test protocols and musculoskeletal models in the MSKBRF Dynamic X‑ray imaging and Motion Analysis Laboratories. By employing state‑of‑the‑art techniques alongside novel concepts, robust institutional and industry collaboration, and continuous engagement with clinicians and patients, the project will enable the development of new, realistic, practical musculoskeletal models to understand knee loading and stability in patients having total knee replacement surgery.
Responsibilities
* Lead the refinement, application and integration of subject‑specific musculoskeletal modelling approaches within the ENGIN‑Knee programme.
* Work with in‑vivo, subject‑specific data generated from Cardiff’s dynamic dual‑plane X‑ray, motion capture and MRI platforms, linked to outputs from in‑vitro, robot‑driven cadaveric testing at Imperial College London.
* Apply, adapt and validate musculoskeletal modelling workflows using existing and newly acquired ENGIN‑Knee datasets.
* Develop and refine subject‑specific or hybrid knee model pipelines informed by imaging, motion analysis and robot‑derived loading data.
* Translate outputs from robot‑driven cadaveric testing into modelling inputs, calibration approaches and validation comparisons.
* Analyse and interpret model predictions of knee kinematics, kinetics, loading and stability across healthy, osteoarthritic and arthroplasty cohorts.
* Contribute to integration of in‑vivo, in‑silico and in‑vitro datasets to support project milestones related to knee instability and model validation.
* Support curation, documentation and dissemination of modelling workflows, derived datasets and outputs for collaborative and open research use.
* Work closely with the Cardiff team, clinicians and project coordinator to ensure modelling activities align with ongoing data collection, governance and project delivery.
* Contribute to reports, publications, presentations and collaborative meetings across the ENGIN‑Knee consortium.
Employment details: Full time (35 hours per week), fixed term from 1st June 2026 to 30th November 2027. Salary: £41,064 – £46,049 per annum (Grade 6). Appointment will not be made above Grade 6 Point 32 (£41,064 per annum).
Equal Opportunities & Diversity
Cardiff University is an equal opportunities employer and actively encourages applications from suitably qualified and eligible candidates regardless of sex, race, disability, age, sexual orientation, gender reassignment, religion or belief, marital status, pregnancy or maternity. For this vacancy we actively encourage women to apply. Flexible working or job share opportunities will also be considered.
Cardiff University is a signatory to the San Francisco Declaration on Research Assessment (DORA), meaning that in hiring and promotion decisions we evaluate applicants on the quality of their research, not publication metrics or the identity of the journal in which the research is published. More information is available at: Responsible research assessment - Research - Cardiff University.
Applications may be submitted in Welsh, and an application submitted in Welsh will not be treated less favourably than an application submitted in English.
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