Autonomous systems have revealed great potential to deliver wide economic and social benefits. One important example is self-driving cars that can reduce traffic congestion, accidents and emissions. Machine learning technologies are powering autonomous systems but are noticeable carbon emitters because of their high computational intensity. The demand for safe and robust autonomous systems in real-world settings has urged researchers to adopt increasingly complex machine learning designs, thus making the computational requirements steep upward.
This PhD project will investigate novel machine learning techniques that have low computational demands, and apply the techniques to ensure the safety and robustness of autonomous systems when in their real-world deployment.
The candidate must have a first class, or a strong upper second class, honours degree in mathematics, electrical engineering, computer science, or a related discipline, as well as good written and spoken communication skills. Previous research experience in control, optimisation and machine learning is desirable but not essential.
How to Apply: Please refer to the following website for details on how to apply: https://www.gla.ac.uk/schools/engineering/phdopportunities/.
Applicants are also welcome to contact Dr Lan ([Email Address Removed]) to discuss other suitable projects that fall into his research areas (see a list of interest at https://www.gla.ac.uk/schools/engineering/staff/jianglinlan/#). I am receiving a large volume of enquiries, so only the suitable candidates will be contacted within a week.