Non-Funded Studentships

We welcome applications from suitably-qualified candidates with their own funding.

You can use our search listing to find the right project for your skills, passion and expertise.

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Machine learning in statistical physics Non-funded

Centre for Fluid and Complex Systems | Engineering, Environment and Computing

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.


Investigation into Selective Catalyst Reduction spray formulation and use of various liquid reductants Non-funded

Institute for Future Transport & Cities | Engineering, Environment and Computing

Studies assume that all the reductant is evaporated at the entry of the SCR domain because of the long mixing length, but this may not be the case in the close-coupled system with a much shorter mixing length. Although the droplet deposition problem could be avoided by other means, such as calibration, this may not work at extreme operating conditions, e.g. low mass flow rate and low temperature. Since the active SCR system will be the major emissions control device in the next generation diesel engines, it is important to have a thorough understanding of such failure modes and find ways to minimize its impact on product development and warranty. This study will be focused on injection of different reductants’ droplets of various fractions into SCR to investigate their impact on system efficiency.


Exploring Mixed-State Wetting of Laser Surface Engineered Polymeric Materials Non-funded

Institute for Future Transport & Cities | Engineering, Environment and Computing

This project will make inroads to achieve a better understanding of the wetting nature of laser surface engineered materials exhibiting a mixed-state wetting regime and will add to the current work being conducted in the field of wetting regimes and wetting transitions.


Intelligent Solar Controller Non-funded

Institute for Future Transport & Cities | Engineering, Environment and Computing

The main focus of this PhD work will be to propose novel techniques for maximum power point tracking in harsh conditions that are theoretically elegant while at the same time practically useful.