PhD Studentship: Quantum Dynamics of Defects in Disordered Alloys University of Birmingham in United Kingdom

[Full tuition fees (Home or International) and tax-free maintenance stipend aligned with UKRI rates (£20,780 per annum for 2025/26), with annual inflationary increases. Competitive award based on academic excellence and research potential.]

PhD Studentship: Quantum Dynamics of Defects in Disordered Alloys at the University of Birmingham offers a unique opportunity to address a central challenge in materials science: predicting the motion of defects such as dislocations and grain boundaries in complex, chemically disordered metallic systems. Traditional models often fail in high entropy alloys, where local fluctuations and structured vibrational spectra result in noisy, history-dependent dynamics governed by quantum and finite temperature dissipation, long-lived memory effects, and collective phonon scattering.

This project aims to develop a rigorous, predictive framework for defect mobility in disordered alloys using non-equilibrium quantum statistical mechanics. The Keldysh Green function formalism will be the core theoretical tool, enabling the incorporation of dissipation, fluctuations, and memory effects beyond classical limits. You will work at the interface of fundamental theory and large-scale computation, developing methods that connect atomistic simulations to effective continuum descriptions of defect motion in infinite disordered media.

Key research directions include:

• Theoretical development: Deriving equations of motion for defects using non-equilibrium Green function techniques, with explicit treatment of phonon-mediated dissipation, memory kernels, and non-adiabatic effects.
• Machine learning integration: Developing physics-informed machine learning approaches to extract reduced dynamical descriptions, such as memory kernels and self-energies, from high-dimensional atomistic simulation data.
• Multiscale numerical implementation: Building workflows that link density functional theory and classical atomistic simulations to effective medium and embedding theories suitable for disordered solids.

Candidate Profile: The ideal candidate is highly motivated and interested in applying fundamental physics to real materials problems. A strong grounding in materials science or theoretical condensed matter physics is highly desirable. Experience or interest in Green function methods, many body theory, solid state physics, numerical linear algebra, or computational physics is preferred. Computational skills, especially with Python and scientific computing, are advantageous. Willingness to engage with high performance computing and data-driven methods is essential. Prior machine learning experience is welcome but not required. International applicants are encouraged to apply.

Training and Career Development: This is not a black box modelling project. The emphasis is on understanding, deriving, and controlling the physics underlying defect dynamics in complex materials. You will gain training in advanced field theoretic methods, large-scale numerical simulation, and modern data science techniques, developing a rare skill set that bridges rigorous theory, computation, and materials modelling. The project is well suited to students aiming for careers in academic research, advanced industrial R&D, or interdisciplinary work at the boundary of physics, data science, and materials engineering.

Funding: The studentship covers full tuition fees (Home or International) and provides a tax-free maintenance stipend aligned with UKRI rates (£20,780 per annum for the 2025/26 academic year), with annual inflationary increases. Funding is awarded competitively based on academic excellence and research potential.

Application Process: Interested candidates are encouraged to make informal enquiries before submitting a formal application. Please send your CV and a brief statement of research interests (highlighting your experience in theoretical physics/scientific computing) to [email protected]. Formal applications should be submitted via the University of Birmingham's online portal. The application deadline is 15 March 2026.

For more details, visit the project webpage.