AniBrain: Advancing Non-Invasive Brain-Machine Interfaces Through Large Language Models

Non-invasive brain-machine interfaces (BMIs) present an exciting frontier for helping individuals to communicate more effectively, especially those with language disbilities. While invasive BMIs have achieved impressive results in restoring or augmenting speech, they raise significant safety concerns due to the surgical procedures required. Conversely, non-invasive BMIs, which use external sensors such as MEG, EEG or fMRI, offer a safer and more accessible approach for a broader range of potential users.

This project aims to develop and refine non-invasive BMIs that integrate state-of-the-art AI-based neural signal processing techniques and large language models (LLMs). By leveraging the powerful linguistic representations of LLMs, we seek to decode and interpret neural activity related to language in a way that is both accurate and robust. Through careful methological design with advanced representation learning and transfer learning technologies, we will optimize the interface to handle individual variability and minimize environmental noise, thereby enhancing communication for those with language impairments. Ultimately, this research will contribute to more accessible, user-friendly, and reliable BMI systems, opening up transformative communication possibilities for individuals with language disabilities and, in the long term, extending these innovations to the wider population seeking safe, non-surgical solutions.

Eligibility

Pursuing a PhD is a journey filled with opportunities and challenges, requiring both academic potential and strong personal qualities. We hope candidates possess the following attributes:

Personal Qualities

Self-discipline: Ability to plan time effectively, maintain research continuity and efficiency, and demonstrate strong self-management, motivation, and goal-setting skills.

Diligence: A willingness to take on complex, long-term research tasks with resilience and commitment, investing time and energy consistently.

Passion: Genuine interest and enthusiasm for academic research, with a strong drive to explore and solve scientific challenges creatively.

Fluent English Proficiency in Listening, Speaking, Reading, and Writing

Candidates should ideally have an IELTS average score of 6.5 or higher (or equivalent), as proficiency in English will be highly beneficial for studying and living in the UK. Academic writing experience in English is a plus.

Academic Background and Technical Skills

Programming experience in artificial neural networks, deep learning, large models, natural language processing, and computer vision is advantageous.

Proficiency in common machine learning frameworks (e.g., PyTorch, TensorFlow, MxNet, Huggingface-Transformer) is highly desirable.

Not required but beneficial: background knowledge in cognitive neuroscience, medical imaging, or bioinformatics.

Funding

This 3.5 year PhD project is fully funded by the Strategic Doctoral Landscape Award (sDLA) Scholarships and is available to home students only. Tuition fees will be paid and the successful candidate will receive an annual tax free stipend set at the UKVI rate (£19,237 for 2024/25).

Interested applicants are encouraged to send their CV and cover letter to [email protected] at their earliest convenience. If we find a suitable candidate, we might end this recruitment earlier than the advertised deadline.

How to apply

Apply online through our website: https://uom.link/pgr-apply-2425

When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees.

Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.

After you have applied you will be asked to upload the following supporting documents:

• Final Transcript and certificates of all awarded university level qualifications
• Interim Transcript of any university level qualifications in progress
• CV
• Supporting statement: A one or two page statement outlining your motivation to pursue postgraduate research and why you want to undertake postgraduate research at Manchester, any relevant research or work experience, the key findings of your previous research experience, and techniques and skills you’ve developed. (This is mandatory for all applicants and the application will be put on hold without it).
• Contact details for two referees (please make sure that the contact email you provide is an official university/work email address as we may need to verify the reference)
• English Language certificate (if applicable)

If you have any questions about making an application, please contact our admissions team by emailing [email protected].

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. We know that diversity strengthens our research community, leading to enhanced research creativity, productivity and quality, and societal and economic impact.

We actively encourage applicants from diverse career paths and backgrounds and from all sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation and transgender status.

We also support applications from those returning from a career break or other roles. We consider offering flexible study arrangements (including part-time: 50%, 60% or 80%, depending on the project/funder).

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