Large Language Models, Neural Encoding, and Decoding of Language

I (Dr. Jingyuan Sun, Assistant Professor, https://sites.google.com/view/jingyuan-sun/home) am delighted to recruit Ph.D. students in collaboration with several distinguished professors in related fields. Together, we aim to nurture and develop doctoral students through research in the following areas:

Area 1: Large Language Models, Neural Encoding, and Decoding of Language

In this area, I will be co-supervising with Prof. Chenghua Lin (Full Professor). Neural encoding examines how external stimuli or cognitive processes are translated into neural signals within the brain, while neural decoding focuses on “reading” information from neural activities—decoding external information from known neural signals. This research aims to investigate how the human brain processes language, exploring similarities and differences between language models and brain-based semantic storage. Additionally, we hope to enhance the performance of non-invasive brain-computer interfaces (BCIs) for language and speech applications.

Area 2: Multimodal Foundational Models for Neuroimages

I will be co-supervising this area with Prof. Goran Nenadic (Full Professor). This research integrates multimodal neuroimaging data into a unified foundational model to capture the relationships among neural activities and brain structure across different modalities. The goal is to unify various dimensions of brain imaging, advancing our understanding of the structural and functional complexities of the human brain. Potential applications include the screening, diagnosis, and treatment of brain disorders.

Area 3: Foundational Models for Multi-Omics Research in Bioinformatics

I will be co-supervising with Dr. Hongpeng Zhou. This research focuses on developing foundational models for multi-omics data, encompassing genomics, transcriptomics, proteomics, and more. By integrating multi-omics data and establishing optimized foundational models, we aim to deepen our understanding of the complex mechanisms underlying certain cancers and to advance personalized medicine applications.

Eligibility

Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline.

Expectations for Candidates

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:

1. Personal Qualities

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

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

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

2. 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.

3. Academic Background and Technical Skills

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

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

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

Funding

For more information, visit our funding page or search our funding database for specific scholarships, studentships and awards you may be eligible for.

Faculty funding scholarships have just been announced (President’s Doctoral Scholarship or Dean’s Doctoral scholarship). Please contact the supervisor to discuss.

Before you apply

We strongly recommend that you contact the supervisors for this project before you apply. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.

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 FSE.doctoralacademy.admissions@manchester.ac.uk.

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).