Our Research Opportunities
Coventry University's research strategy is underpinned by a £250m investment in research, our estate and facilities. It also:
- enables our academics to apply fresh and original approaches to key research challenges
- informs their teaching
- provides opportunities for postgraduate students to participate in major research projects.
We currently offer a variety of PhD studentships to outstanding applicants, to areas of research undertaken by our Research Centres and our industrial collaborations.
To find a PhD for you, search by topic/subject in the bar below or filter by research area/centre on the available drop-down box.
Parallel simulations with population annealing
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.
Advanced and transferable time series analysis methods for anomaly prediction
The purpose of this project is to develop generic new methods and tools in the detection and prediction of anomalies in time series based on novel concepts like sliding correlation coefficient, natural time analysis and machine learning with applications in a range of diverse systems. The first priority here is the outcome of the applications to constitute independent studies. Finally, since, the impact of this project will be both direct and valuable will improve the engagement between academia and industry.
Defect processes in novel materials for energy and nuclear applications. Automated techniques on ab initio calculations
The first priority here is to investigate novel materials for a range of safety and energy applications. Furthermore, the question here is whether it is possible to combine Artificial Intelligent methods and/or develop algorithms to reduce the amount of the demanding calculations. Currently, this topic has a high and direct impact both in academia and industry, as these methods will be transferable in numerous principles such as aerospace, mechanical and automotive engineering, power electronics.