UNIVERSITY OF LIVERPOOL · UNITED KINGDOM
Generative AI Models for Materials Discovery
PhD · Taught in en · UCAS CCPR176
At a glance
42 mo
Duration
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IELTS
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Tuition / yr
en
Language
PhD
Level
- PhDDegree Level
- 3.5 yearsFunding Duration
- UKRI Minimum Rate (£21,805 p.a.) + Research Training Support GrantStipend and Funding
- October 2026Start Date
- Chemistry/AI/Materials ScienceSubject Area
This PhD project focuses on developing advanced generative machine learning models to accelerate the discovery of new inorganic solid-state materials, crucial for innovations in energy storage, catalysis, semiconductors, and quantum technologies. The current methods for designing these materials are challenging, highlighting the importance of improved methodologies. The project will explore cutting-edge generative modelling techniques, such as diffusion models and large language models, integrating them with chemically informed constraints and first-principles calculations. The aim is to create AI-driven crystal structure prediction workflows that can accurately generate potential experimental targets, predict their stability and properties, and ultimately push the boundaries of materials discovery beyond existing paradigms. You will join a multidisciplinary research group at the intersection of solid-state materials science and AI, with access to high-performance computing resources and opportunities to collaborate with experimentalists. This studentship is ideal for individuals with a background in computational materials science, machine learning, or artificial intelligence, who possess strong Python coding skills. Familiarity with ML frameworks like PyTorch/TensorFlow, graph/neural networks, materials science, crystallography, or solid-state chemistry would be advantageous.
Careers
This PhD provides a strong foundation for a career in cutting-edge research and development within academia or industry, focusing on the application of AI in materials science.
- AI Researcher (Materials Science)
- Computational Materials Scientist
- Machine Learning Engineer (Scientific Computing)
- R&D Scientist
- Data Scientist (Chemistry/Physics)
Frequently asked questions
- What are the entry requirements for the Generative AI Models for Materials Discovery PhD?
- You need a Master's degree or equivalent in Computer Science or a Physical Science. A First Class Honours Bachelor's degree in an appropriate field can be considered for exceptional candidates. Strong Python coding skills are essential, and experience with ML frameworks or materials science is advantageous.
- Does this PhD programme cover tuition fees and living costs for international students?
- Yes, the UKRI funded studentship covers full tuition fees and provides a maintenance grant at the UKRI minimum rate, starting at £21,805 for 2026/27. A Research Training Support Grant is also provided.
- Are there specific scholarships available for international students to cover the fee difference?
- Yes, a limited number of International Fee Difference Scholarships may be available for outstanding international students to cover the difference between international fees and the UKRI funding.
- What is the duration of the Generative AI Models for Materials Discovery PhD and when does it start?
- The PhD programme has a funding duration of 3.5 years and is set to start on October 1, 2026.
- How do I apply for the Generative AI Models for Materials Discovery PhD?
- You should first contact the supervisors, Professor Matt Rosseinsky (m.j.rosseinsky@liverpool.ac.uk) or Professor Rahul Savani (Rahul.Savani@liverpool.ac.uk), to express your interest. Then, prepare your application documents and submit your application through the University of Liverpool's online postgraduate research application portal by August 31, 2026.
- What are the potential career outcomes after completing this PhD?
- This PhD prepares you for roles such as an AI Researcher in Materials Science, Computational Materials Scientist, Machine Learning Engineer, R&D Scientist, or Data Scientist in scientific fields.
Entry requirements
Master's Degree or equivalentIn Computer Science or a Physical Science
Bachelor's DegreeFirst Class Honours in an appropriate field (for exceptional candidates)
Applicants are encouraged to highlight relevant experience with Python, ML frameworks (PyTorch/TensorFlow), graph/neural networks, and familiarity with materials science, crystallography, or solid-state chemistry. Experience with writing code is essential.
Fees
Tuition (international)Full tuition fees covered by UKRI funding for eligible students. A limited number of scholarships may be available to cover the fee difference for outstanding international students.
Tuition (home)Covered by UKRI funding.
LivingMaintenance grant paid at the UKRI minimum rate, starting at £21,805 for 2026/27, increasing annually.
The studentship covers full tuition fees and a maintenance grant for 3.5 years. A Research Training Support Grant is also provided for consumables and conference attendance.
How to apply
1. Step 1: Contact SupervisorsReach out to Professor Matt Rosseinsky (m.j.rosseinsky@liverpool.ac.uk) or Professor Rahul Savani (Rahul.Savani@liverpool.ac.uk) to express your interest and discuss the project.
2. Step 2: Prepare Application DocumentsGather necessary documents including a research proposal, university transcripts and certificates, passport details (for international applicants), English language certificates (if applicable), a personal statement, CV, and contact details for two referees.
3. Step 3: Complete the Online Application FormSubmit your application via the University of Liverpool's online postgraduate research application form. Ensure you include the project title and reference number CCPR176.
4. Step 4: Submit ApplicationRegister and apply online through the University of Liverpool application portal. You will receive an email acknowledgment upon submission.
Scholarships
UKRI Funded StudentshipFull tuition fees + maintenance grant (£21,805 p.a. starting rate)
International Fee Difference ScholarshipCovers fee difference for international students
Accreditation
The PhD is awarded by the University of Liverpool.
Frequently asked questions
What are the entry requirements for the Generative AI Models for Materials Discovery PhD?
+
You need a Master's degree or equivalent in Computer Science or a Physical Science. A First Class Honours Bachelor's degree in an appropriate field can be considered for exceptional candidates. Strong Python coding skills are essential, and experience with ML frameworks or materials science is advantageous.
Does this PhD programme cover tuition fees and living costs for international students?
+
Yes, the UKRI funded studentship covers full tuition fees and provides a maintenance grant at the UKRI minimum rate, starting at £21,805 for 2026/27. A Research Training Support Grant is also provided.
Are there specific scholarships available for international students to cover the fee difference?
+
Yes, a limited number of International Fee Difference Scholarships may be available for outstanding international students to cover the difference between international fees and the UKRI funding.
What is the duration of the Generative AI Models for Materials Discovery PhD and when does it start?
+
The PhD programme has a funding duration of 3.5 years and is set to start on October 1, 2026.
How do I apply for the Generative AI Models for Materials Discovery PhD?
+
You should first contact the supervisors, Professor Matt Rosseinsky (m.j.rosseinsky@liverpool.ac.uk) or Professor Rahul Savani (Rahul.Savani@liverpool.ac.uk), to express your interest. Then, prepare your application documents and submit your application through the University of Liverpool's online postgraduate research application portal by August 31, 2026.
What are the potential career outcomes after completing this PhD?
+
This PhD prepares you for roles such as an AI Researcher in Materials Science, Computational Materials Scientist, Machine Learning Engineer, R&D Scientist, or Data Scientist in scientific fields.