Job Description We are seeking an enthusiastic, high-performing PhD candidate to join PRECISE and contribute to an innovative project titled: " Towards precision offloading for the prevention of diabetic foot ulcers. " Diabetic foot ulcers remain a major cause of hospitalisation and amputation worldwide.
PRECISE researchers are developing new approaches to personalise offloading and improve long-term outcomes for people with diabetes.
As part of this larger program, this project aims to develop clinically applicable methods to understand and manage mechanical loading in the foot to prevent ulcer recurrence.
This PhD project will focus on integrating plantar pressure data, gait analysis, footwear/orthotic design and real-world activity patterns to optimise offloading strategies.
The candidate will work closely with clinical partners to translate these methods into practical tools and protocols that support clinicians in tailoring offloading interventions for individual patients.
Project Highlights Work within a world-leading centre specialising in precision health technologies.
Develop and test precision offloading strategies to reduce ulcer recurrence in people with diabetes.
Engage with clinicians, podiatrists and hospital partners to translate research into real-world clinical practice.
Access cutting-edge facilities, including wearable sensor labs, motion analysis systems, in-shoe pressure measurement, 3D imaging and digital health analytics platforms.
Contribute to research that directly reduces the burden of diabetic foot disease, hospitalisation and amputation.
Qualifications To be successful in this role, you will demonstrate: A strong academic background in: Biomechanics, Biomedical Science, Engineering, Data Science, Health Technology, Podiatry, Physiotherapy, or a closely related field.
Research experience in one or more of the following (desirable but not essential): Gait analysis or lower-limb biomechanics Plantar pressure measurement or offloading interventions (e.g. footwear, insoles, orthoses, casts) Wearable sensor data collection and analysis Machine learning, AI or advanced statistics Clinical or health-related research involving people with diabetes Evidence of collaborative skills and the ability to work with interdisciplinary research and clinical teams.
A demonstrated passion for improving outcomes for people with diabetes and advancing precision, person-centred foot care.
Academic Eligibility Requirements Applicants must have completed, or be expected to complete: A Bachelor's degree with Class I Honours, or A Master's degree (AQF Level 9) with a substantial research component, or Be assessed by Griffith University as having equivalent research experience (as per HDR Scholarship Procedure).