Available
Project number:
2025_80
Start date:
October 2025
Project themes:
Main supervisor:
Senior Lecturer in Engineering
Co-supervisor:
Prof Adil Mardinoglu, Faculty of Dentistry, Oral & Craniofacial Sciences
Additional Information:
Closed-loop experimentation platform to enable autonomous discovery lab
In biomedical research conventional experimentation workflows lead to inefficient experiment space exploration and slow evolvement from technology discovery to scale-up. This is caused by under-utilisation of data from previous experiments and large time gaps between experimental design and execution in conventional experimentation with human decision-making. Transitioning from lab discovery to technology scale-up can be resource-intensive.
The PhD programme aims to develop a digital closed-loop experimentation platform which will autonomously plan and drive high-throughput experiments (including laboratory and computational experiments) to accelerate the health-related discovery and development e.g. drug discovery. Specifically, this PhD will build upon our existing research capacity, develop a surrogate-based Bayesian optimisation as experiment planner. building upon supervisor team’s lab capacities and complementary expertise on systems medicine, mathematical and computational modelling, this PhD project will be well supported.
The developed platform will be tested in laboratory experiments on autonomous drug discovery, where our developed AI-driven retro-biosynthesis methods (existing research co-supervised by first and second supervisors) will be applied to identify biosynthetic reaction pathways and guide design optimisation and production of new drugs. This PhD will be exposed to an inclusive, supportive yet vibrant environmental and have the opportunities to collaborate with existing team to develop a modular autonomous lab system, which integrates task-oriented lab experiment flows.
This project will also test the closed-loop experimentation platform in computational lab on computational experiments such as metabolic pathway reconstruction. This would enable a better understanding of how certain diseases develop and identify key intermediates and enzymes involved to facilitate therapeutic targeting.
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 30 January 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in March 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at
