Ehsan Azmoodeh

This PhD position at Xi’an Jiaotong-Liverpool University (XJTLU) focuses on developing a unified theory for reinforcement learning. The project addresses the challenge of scatteredness among various models and algorithms in reinforcement learning by aiming to connect different branches through a comprehensive theoretical framework. The research will involve rigorous mathematical proofs, statistical modelling, and the fusion of existing theoretical approaches to create a unified algorithmic structure applicable to practical problems. Supervised by Professor/Dr Keqin Liu (XJTLU), Professor/Dr Hui Zhang (XJTLU), and Professor/Dr Ehsan Azmoodeh (University of Liverpool), the student will conduct the majority of research at XJTLU in Suzhou, China, with the possibility of a short-term research visit to the University of Liverpool if required by the project. Upon successful completion, the PhD degree will be awarded by the University of Liverpool (UK). The studentship is available for three years, subject to satisfactory progress. It covers tuition fees (currently RMB 99,000 per annum) and provides up to RMB 16,500 for participation at international conferences. The position is open to all qualified candidates regardless of nationality. Applicants must hold a Master's degree with Merit and a Bachelor's degree with first-class or upper second-class honors. Exceptional candidates with only a Bachelor's degree may be considered individually. Evidence of good spoken and written English is essential, with an IELTS (or equivalent) score of 6.5 or above required if the first language is not English. To apply, email [email protected] with the project title in the subject line and attach your CV, two formal reference letters, personal statement, certificates of English language qualifications, full academic transcripts, verified certificates of education qualifications, and a PDF copy of your Master Degree dissertation or equivalent writing sample. Applications are accepted year round. For further information, visit the XJTLU doctoral admissions and scholarship pages or contact the principal supervisor directly. This opportunity is ideal for candidates interested in mathematical modelling, statistics, and advanced algorithmic research in reinforcement learning.