Spin models with random fields
Eligibility: UK/EU graduates with the required entry requirements
PhD funding award: Full fee and stipend
Duration: Full-Time – between three and three and a half years fixed term
Application deadline: 10 December 2019
Interview dates: Will be confirmed to shortlisted candidates
Start date: January 2020
Enquiries may be addressed to Martin Weigel.
This project is focused on the physics of magnetic systems with impurities as modelled by spin systems with quenched disorder. From previous research we have a good understanding of the physics of the random-field Ising model, but generalisations to systems with more than two states have rarely been studied. Such systems have manifold applications in magnetic grains, anisotropic orientational glasses, randomly diluted molecular crystals and related problems. In the present project the doctoral researcher will work with a combination of exact and heuristic combinatorial optimisation algorithms based on graph cuts and generalised-ensemble Monte Carlo simulations to uncover the phase diagram and related behaviour of the random-field Potts model.
Fully-funded studentship available (£15,009 stipend and full fees paid).
- The candidate will work with our extensive High-Performance Computing (HPC) facilities, including a GPU enabled 3000-core cluster
- Our research strategy is underpinned by a £250m investment in research and facilities
- Dedicated Doctoral College and Centre for Research Capability Development deliver high quality professional support for researchers, from PhD to Professor
- Free training: research career planning, managing your doctorate, research communication skills, research ethics, research impact, research integrity, research methods and research supervision
- Coventry is a member of the Doctoral Training Alliance (DTA), the largest multi-partner and only nationwide doctoral training initiative of its kind.
- A minimum of a 2:1 first degree in a relevant discipline/subject area with a minimum 60% mark in the Project element or equivalent with a minimum 60% overall module average
- In the event of a first degree classification of less than 2:1, a Masters Degree in a relevant subject area will be considered as an equivalent. The Masters must have been attained with overall marks at minimum merit level (60%). In addition, the dissertation or equivalent element in the Masters must also have been attained with a mark at minimum merit level (60%)
- Plus the potential to engage in innovative research and to complete the PhD within a three-year period of study
- A minimum of English language proficiency (IELTS overall minimum score of 7.0 with a minimum of 6.5 in each component)
- a BSc or MSc degree in Physics, Mathematics, or Computer Science
- some experience in statistical physics and/or machine learning
- programming skills in C/C++, Python, Fortran or other suitable languages