About the role
Join theCEREBRIS project, a flagshipEuropean Innovation Council (EIC) Pathfinder programme developing next-generation AI and neurotechnology to transform stroke diagnosis, prognosis and rehabilitation. Working within theBath Institute for the Augmented Human, you will collaborate with leading researchers and an international consortium to deliver cutting-edge translational research.
In this role you will:
- Develop and apply advanced AI methods, including multimodal foundation models and deep learning, to analyse complex neurotechnology and clinical datasets.
- Work with multimodal data including EEG, fNIRS, MRI, movement analysis and clinical assessments to develop explainable AI for stroke recovery.
- Publish high-impact research, contribute to international collaborations, and present your work at leading conferences.
- Help shape the future of AI-driven neurotechnology within a multidisciplinary team spanning computer science, engineering, neuroscience and clinical research.
As a member of Research Staff at the University of Bath, you will be encouraged to take up a minimum of 10 days professional development pro-rata per year.
A lower grade offer may be made (Grade 6) with comparable reduction in responsibilities & amendment in job title to Research Assistant, if a suitable applicant cannot be found to fill the Grade 7 position. Applicants will need to be within 6 months of their course completion date and will be promoted to Research Associate once their PhD has been awarded.
About you
We are looking for a motivated researcher with a passion for applying AI to solve real-world healthcare challenges. You will have strong technical skills, experience with neurophysiological data, and enjoy working collaboratively within a multidisciplinary research environment.
Essential:
- A PhD (or equivalent experience and professional qualification) in Artificial Intelligence, Computer Science, Machine Learning, Biomedical Engineering, Computational Neuroscience or a closely related discipline.
- Experience developing AI or machine learning methods using frameworks such as PyTorch and/or TensorFlow.
- Hands-on experience acquiring, processing & analysing EEG and/or functional near-infrared spectroscopy (fNIRS) data.
- Experience developing robust signal processing and/or machine learning pipelines for complex datasets.
- Evidence of research excellence, including publications or the potential to publish in high-quality peer-reviewed journals.
- Excellent programming, analytical, written and verbal communication skills.
- Ability to work independently and collaboratively within a multidisciplinary research team.
- Excellent organisational skills with the ability to manage competing priorities and meet project deadlines.
- A commitment to conducting research to the highest professional & ethical standards.
Desirable:
- Experience with multimodal AI, foundation models, generative AI or representation learning.
- Experience integrating neurophysiological data with neuroimaging, movement or clinical datasets.
- Experience with GPU-accelerated computing or high-performance computing environments.
- Experience contributing to research proposals, supervising students or working within international collaborative research projects.
Further information
This is a full-time (36.5 hours per week) fixed-term role lasting approximately 36 months.
For an informal discussion regarding the role please contact Damien Coyle at .
We consider ourselves to be a university where difference is celebrated, respected and encouraged. We have an excellent international reputation with staff from over 60 different nations and have made a positive commitment towards gender equity and intersectionality receiving a Silver Athena SWAN award. We truly believe that diversity of experience, perspectives, and backgrounds will lead to a better environment for our employees and students and encourage applications from all genders, backgrounds, and communities, particularly from under-represented groups, and value the positive impact that will have on the university. We are committed to maintaining a safe and secure environment for our students, staff, and community.
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