The Doctoral College and Centre for Research Capability Development was established in April 2017. The college and centre provide high quality professional support for researchers, from PhD to Professor, including delivery of doctoral programmes, professional training and development support for researchers. The Doctoral College is responsible for the recruitment of, and support to, all enrolled research students and for supporting our team of research supervisors.
The Centre for Research Capability Development leads on evidence-based training and development initiatives for all researchers.
The College and Centre is governed by a steering committee. Find out more here DOCTORAL COLLEGE: Governance.
Click on each tab below to learn more about the college and centre’s work, discover the innovative training and development opportunities available to all researchers at Coventry University, and learn how you can join us on one of our doctorate programmes. Find out more about research studentship opportunities.
Find out more information about studentships at Coventry University before making your application to us.
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 offer fully-funded, self-funded and part-funded PhD studentships to outstanding applicants, many of which are within 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.
Optimisation of Multi-Material Crash Structures Beyond 2025
The overall aim of this project is to define, implement and critically assess an optimisation algorithm / methodology for optimisation of multi-material vehicle crash structures. This will be achieved via numerical simulation (primarily finite element based) and, where appropriate, physical testing.
Permeability and slip in porous walls of particulate filters
The purpose of this project is experimental, analytical and numerical investigation of the high temperature effects in particulate filters. Permeability, slip effect and, consequently, friction losses within the porous walls will need to be studied, and new correlations for the relevant parameters will be developed. These correlations are expected to be based on solid fluid dynamics principles, thus providing an invaluable tool for design of the new generation after treatment systems.
An investigation into topology optimisation of non-isotropic components
The overall aim of this project is to determine the effects of using “truly non-isotropic topology optimisation” upon the final design of vehicle body structures. This will be achieved via numerical simulation (primarily finite element based) and, where appropriate, physical testing.
Machine learning in statistical physics
The student will use deep neural networks to quantitatively describe phase transitions in pure and disordered spin systems. Advanced techniques such as GANs will be employed to directly sample configurations of such systems. As a result, the student will be able to map out the utility of such methods for research in statistical physics and potentially open up exciting new avenues resulting from combining approaches from different disciplines.
Characterisation of multiphase turbulence by optical measurements in refractive index-matched system
To the date, no reliable measurements of turbulence spectrum and two-phase velocity fields are obtained even in simple configurations such as pipe flow. We will advance index matching as a tool for two-phase flow studies while focussing on characterisation of two-phase turbulence. The project will initiate a new field of applying rigorous Fluid Dynamics optical instruments to quantitative investigation of two-phase flows.