At a Glance
- Tasks: Develop cutting-edge algorithms for digital healthcare and real-time AI models.
- Company: Brunel University London, a leader in engineering and technology research.
- Benefits: Generous leave, hybrid working, and excellent training opportunities.
- Other info: Collaborate with industry partners and publish at top AI/ML conferences.
- Why this job: Join a dynamic team and make a real impact in AI and healthcare.
- Qualifications: Strong knowledge of AI models and experience in digital healthcare preferred.
The successful candidate will contribute to EU projects with funding from Innovate UK and UKRI to develop wireless communication optimisation algorithms for digital healthcare applications and low‑latency real‑time AI inference models for markerless pose detection. Collaboration with industry partners across the UK/EU is required.
Key Responsibilities
- Develop wireless communication optimisation algorithms for digital healthcare applications.
- Design low‑latency real‑time AI inference models for markerless pose detection.
- Collaborate with industrial partners for research and experimentation.
- Publish findings at leading AI/ML conferences such as CVPR, ICLR, and NeurIPS.
Qualifications & Knowledge
- Strong knowledge of Agentic AI, large language models (LLMs), and Vision‑Language‑Action (VLA) models.
- Preference for candidates with publications in leading AI/ML conferences.
- Experience in digital healthcare applications or real‑time AI models is a plus.
Employment Details
- Location: Brunel University of London, Uxbridge Campus
- Role: Full‑time, fixed‑term (4 months or until 28 Feb 2027, whichever is earlier)
- Salary – Research Assistant: R1 Grade £37,118 to £39,144 per annum inclusive of London weighting (potential progression).
- Salary – Research Fellow: R1 Grade £41,292 to £44,762 per annum inclusive of London weighting (potential progression).
- Hours: Full‑time.
Benefits
- Generous annual leave package
- Discretionary university closure days
- Excellent training and development opportunities
- Occupational pension scheme
- Health‑related support
- Hybrid working approach
Application Process
Please upload your CV, including publications, and a cover letter summarising your experience and achievements. For an informal discussion, email Professor Kezhi Wang at Kezhi.Wang@brunel.ac.uk.
Closing Date: 6 August 2026
EEO Statement: Brunel University London is fully committed to creating and sustaining a fully inclusive workforce culture. We welcome applicants from all backgrounds and communities, particularly those who are currently under‑represented.
Research Assistant/ Research Fellow - 16945 in Uxbridge employer: Brunel University of London
Brunel University of London is an exceptional employer, offering a dynamic work environment in Uxbridge that fosters academic excellence and innovation. With a strong emphasis on research-driven teaching, employees benefit from generous annual leave, comprehensive training opportunities, and a supportive community that encourages professional growth and collaboration.
Contact Details:
Brunel University of London Recruitment Team
