Research Fellow in AI

About the University
Manchester Metropolitan University is one of the UK's most ambitious and modern universities, with a history dating back to 1824. Ranked among the top 200 young universities globally, 90% of our research impact is world-leading or internationally excellent (REF 2021). Based in the heart of Manchester, we benefit from strong links to the region's growing digital and healthcare innovation sectors.

The Department of Computing and Mathematics, within the Faculty of Science and Engineering, is a dynamic and research-active community comprising over 80 academic staff and 2,000 students. The department has an established track record in securing competitive research funding, with a diverse portfolio of projects supported by UKRI research councils, charitable foundations, the EU, and Innovate UK. It maintains close collaborations with the NHS, government bodies, and industry—particularly within the region's flourishing digital sector. Our core research strengths include Artificial Intelligence and Data Science, Machine Intelligence, Human-Centred Computing, Cybersecurity, and Mathematical Modelling, underpinned by a strong culture of interdisciplinary collaboration and a commitment to delivering global impact.

About the role
We are seeking an ambitious and highly motivated Research Fellow in AI to contribute to a transformative, cross-faculty project focused on personalising Parkinson's disease treatment through advanced Digital Twin technology.

Based in the Department of Computing and Mathematics, you will lead the design and development of AI-driven models applied to complex healthcare and neuroimaging datasets, contributing to the creation of a personalised Digital Twin of the brain's motor system—a virtual model that enables precise, patient-specific treatment planning.

You will work closely with an expert multidisciplinary team that spans two faculties: Professor Nicola Ray and Dr Nelson Trujillo-Barreto from the School of Psychology (Faculty of Health and Education), and Professor Moi Hoon Yap and Professor Liangxiu Han from the Department of Computing and Mathematics (Faculty of Science and Engineering). The project is also delivered in partnership with senior clinicians from Salford Royal Hospital and The Walton Centre, aiming to enhance clinical practice and empower patients through innovation.

This is a unique opportunity to develop advanced AI methodologies to a real-world clinical challenge and to collaborate closely with neuroscientists, clinicians, engineers, and people living with Parkinson's disease.

Key Responsibilities

• Lead the design and implementation of predictive AI models using multimodal data (e.g. time-series signals, neuroimaging, clinical records) for healthcare applications.
• Contribute to the development of a Digital Twin of the brain's motor system to support model-based control of Deep Brain Stimulation (DBS) and personalised treatment strategies for Parkinson's disease.
• Develop and optimise scalable data processing pipelines, including GPU acceleration, cloud computing, and distributed architectures, to enable efficient analysis of large-scale biomedical datasets.
• Collaborate with clinical and academic partners, both internally and externally, to ensure scientific rigour, clinical relevance, and impactful interdisciplinary outcomes.
• Produce and disseminate high-quality research outputs, including peer-reviewed publications, conference presentations, and engagement with stakeholders; contribute to the preparation of research funding proposals.
• Engage in scholarly development and network-building, supporting your own academic career progression while enhancing the University's research culture and collaborative profile.

Qualifications:

• PhD in Computer Science/AI or a closely related field.
• Extensive research experience in machine learning, deep learning, and self-supervised learning, with a strong track record of applying these techniques to healthcare or biomedical challenges.
• Demonstrable expertise in processing and analysing large-scale, multimodal datasets (e.g. neuroimaging, time-series signals, clinical records) for predictive modelling and decision support.
• Proficiency in programming languages such as Python (and/or Java, C/C++), with hands-on experience using AI frameworks (e.g. PyTorch, TensorFlow) and relevant libraries.
• Practical experience in scalable data processing, including the use of parallel computing, cloud platforms, and distributed systems for efficient, high-volume data analysis.
• A strong publication record in high-impact peer-reviewed journals and international conferences, evidencing independent and original research contributions.
• Proven ability to work within interdisciplinary research teams, including collaborations with clinical or healthcare professionals.
• Excellent written and verbal communication skills, including experience in presenting complex research findings to academic and non-academic audiences.

Desirable:

• Knowledge of Digital Twin systems, control theory, or computational modelling of neurological or physiological systems. Experience with physically informed AI or control systems.
• Experience with research funding, including contributing to or leading successful grant applications.
• Experience in supervising or mentoring postgraduate students or junior researchers.

To learn more about the role and requirements, please read the Job Description (available on the university's website, accessed by the 'Apply' button). 

To apply:

• If you would like to apply, please take the time to consider the essential criteria in the job description and provide us with a CV that demonstrates your suitability for the role.
• For an informal discussion regarding the requirements of the roles, please contact Professor Liangxiu Han (l.han@mmu.ac.uk) or Professor Moi Hoon Yap (M.Yap@mmu.ac.uk) for details.

We believe in working together, sharing knowledge and valuing everyone's contributions. Develop your skills, further your knowledge and be part of a team who are transforming lives, every single day!

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Manchester Metropolitan University is committed to supporting the rights, responsibilities, dignity, health and wellbeing of staff and students through our commitment to equality, diversity and inclusion. We promote applications from all sections of the community, irrespective of background, belief or identity, recognising the benefits that a diverse organisation can bring and particularly encourage applications from groups which are underrepresented in the University workforce. We recognise the benefits and importance of an environment that supports flexible working and are open to conversations about this, as well as any reasonable adjustments required throughout the application process.