Our Research Opportunities
Coventry University £7million Postgraduate Research Studentship fund
Coventry University is a top-50 placed (Complete University Guide 2019,) globally-connected university with research collaborations across the planet and multinational research staff and postgraduate researchers. We give as high a priority to top quality research as we give to top quality teaching. 92% of our research was rated as ‘world-leading’, ‘internationally excellent’ or ‘recognised internationally’ (REF 2014 – assessed every seven years)
Coventry University has a growing reputation as a successful research university with a strong international profile, investment and expertise in professional development for researchers, and an excellent track record in delivering programmes to develop research capability with international partners. We have committed £250m to research, through investment in our estate, infrastructure and facilities, and programmes and initiatives that support researchers.
We have a network of 14 multi-disciplinary Research Centres and a Doctoral College and Centre for Research Capability and Development which offers a home and a community to our 700 researchers, working on an expansive portfolio of research across the themes of: Safety and Security, Sustainability and Resilience, Health and Well-being, Intelligent Products and Processes, Creative Cultures and Global Learning, Education and Attainment.
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.