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**
- **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.
- 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 in **supervi