Summary
The University of Manchester invites applications for a fully funded 3.5-year PhD Studentship in Theoretical Condensed Matter Physics under the project “Neural Quantum States for Automated Discovery of Emergent Quantum Phases in Two-Dimensional Materials.”
This project develops advanced computational frameworks combining density functional theory, machine learning, and neural quantum states (NQS) to discover and characterize emergent quantum phases in twisted and layered 2D materials. The research is based at the National Graphene Institute, offering access to a world-leading environment in quantum materials research.
PhD Scholarship in Neural Quantum States & 2D Quantum Materials – University of Manchester, UK
Designation
PhD Studentship (DKO Fellowship Award)
Scholarship Details
| Particulars | Details |
|---|---|
| Position | PhD Studentship – Neural Quantum States in 2D Materials |
| Institution | University of Manchester |
| Department | Physics and Astronomy |
| Research Theme | Theoretical Condensed Matter Physics |
| Duration | 3.5 Years |
| Start Date | October 2026 |
| Location | Manchester, United Kingdom |
| Funding Type | DKO Fellowship (Fully Funded) |
| Stipend | £21,805 per year (UKRI rate, tax-free; annual uplift expected) |
| Tuition Fees | Fully Covered |
| Application Deadline | 31 May 2026 |
| Application Portal | uom.link/pgr-apply-2425 |
Research Area
- Theoretical Condensed Matter Physics
- Quantum Materials & 2D Materials
- Neural Quantum States (NQS)
- Machine Learning in Physics
- Many-Body Quantum Systems
- Density Functional Theory (DFT)
- Moiré and Van der Waals Heterostructures
- High-Performance Scientific Computing
- Emergent Quantum Phases
Location
Manchester
National Graphene Institute, University of Manchester, UK
Eligibility / Qualification
Applicants should have or expect to achieve:
Essential Requirements
- Minimum 2:1 Bachelor’s degree or Master’s degree (or equivalent) in:
- Physics
- Applied Physics
- Materials Science
- Mathematics
- Engineering or related disciplines
- Strong interest in:
- Quantum materials
- Theoretical or computational physics
- Basic programming or computational skills are highly desirable
Preferred Skills
- Knowledge of condensed matter physics
- Experience with electronic structure methods (DFT, tight-binding models)
- Familiarity with machine learning or scientific computing
- Interest in high-performance computing (HPC)
Job Description
The PhD candidate will develop an advanced computational pipeline for discovering and characterizing emergent quantum phases in 2D materials.
Key Research Tasks
- Electronic structure modeling
- Use DFT and Wannier-based tight-binding methods
- Construct realistic models of twisted and layered materials
- Many-body quantum simulations
- Apply Neural Quantum States (NQS) methods
- Solve interacting electron systems beyond traditional methods
- Automated phase discovery
- Predict energies, band gaps, correlation functions
- Identify quantum phase boundaries and emergent states
- Materials exploration
- Study moiré systems and van der Waals heterostructures
- Investigate phenomena such as:
- Correlated insulating states
- Charge order
- Fractional Chern phases
- Computational framework development
- Build automated pipelines combining ab-initio and machine learning methods
- Develop scalable tools for quantum materials discovery
Scholarship Benefits
- Fully funded PhD (tuition fees covered)
- Annual tax-free stipend: £21,805 (UKRI rate, 2026/27)
- 3.5 years of funding
- Access to high-performance computing facilities
- Research at the National Graphene Institute
- Collaboration with leading experimental and theoretical physicists
- Opportunity to contribute to cutting-edge quantum materials discovery
- Strong interdisciplinary research environment
How to Apply
Application Process
Apply online via:
👉 uom.link/pgr-apply-2425
Before Applying
Candidates are strongly advised to contact the supervisor:
Dr. James McHugh
📧 james.mchugh@manchester.ac.uk
Applicants should include:
- Current academic status
- Academic background
- Relevant experience
- A short motivation statement for the PhD project
Last Date for Apply
📅 31 May 2026
Early application is strongly recommended as the position may close before the deadline.






