Parallel simulations in statistical physics
Eligibility: UK/EU & International students with the required entry requirements
Award Details: Bursary plus tuition fees (UK/EU)
Duration: Full-Time – three and a half years fixed term
Application deadline: 4pm, 18 March 2019
Interview dates: TBC
Start date: May 2019
Informal enquiries are essential before application; contact Martin Weigel to discuss this opportunity.
Coventry University has been voted ‘Modern University of the Year’ three times running by The Times/Sunday Times Good University Guide. Ranked in the UK’s top 15 (Guardian University Guide), we have a global reputation for high quality teaching and research with impact. Almost two-thirds (61%) of our research was judged ‘world leading’ or ‘internationally excellent’ in the Research Excellence Framework (REF) 2014.
Population annealing is a sequential Monte Carlo scheme applicable to studying systems in statistical, condensed matter and biophysics that is potentially able to make use of highly parallel computational resources as provided by petaflop and future exaflop machines. Additionally, it promises the accelerated simulation of systems with complex free-energy landscapes such as spin glasses, biopolymers and optimisation problems. This research project is geared towards gauging the potential of this exciting new method and to developing it further to adapt it to a variety of applications. This includes the study of optimised schemes for choosing the simulation parameters such as the population size, sweep and temperature protocols, the adaptation of the methods to new ensembles and underlying basic simulation techniques. Additional aspects involve assessments of the relative performance with respect to more traditional techniques and the development of estimation methods for statistical and systematic errors.
This exciting research project is being conducted with expertise from both Coventry University and the University of Leipzig, Germany The doctoral researcher will spend time at each institution and will be co-supervised by Martin Weigel (Coventry University) and Wolfhard Janke (University of Leipzig).
Possible fully-funded studentship available (up to £15,000 stipend and fee waiver)
- 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.
Entry criteria for applicants to PHD (standard)
- 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%).
- 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