Surrogate-assisted many-objective optimisation

This PhD position will focus on the intersection of Bayesian optimisation and evolutionary computation for large-scale multi-/many objective optimisation. The successful applicant will study at the University of Surrey in the first two years of the programme, supervised by Dr Yunpeng Li and co-supervised by Prof. Yaochu Jin, and the third and fourth year at SUSTech supervised by Prof. Hisao Ishibuchi.

Start date
1 October 2019
Duration
4 years
Application deadline
Funding information

A full PhD studentship of up to 4 years is available for the Joint PhD programme between the University of Surrey in Guildford, UK and the Southern University of Science and Technology (SUSTech) in Shenzhen, China. https://gs.sustech.edu.cn/boshilianpei2020/1727

About

This PhD position will focus on the intersection of Bayesian optimisation and evolutionary computation for large-scale multi-/many objective optimisation. The successful applicant will study at the University of Surrey in the first two years of the programme, supervised by Dr Yunpeng Li and co-supervised by Prof. Yaochu Jin, and the third and fourth year at SUSTech supervised by Prof. Hisao Ishibuchi.

University of Surrey conducts intensive research in artificial intelligence, 5G, internet of things, and psychology and sociology. You will be part of the Nature Inspired Computing and Engineering (NICE) Research Group in the Department of Computer Science. The NICE group is engaged in research in evolutionary computation, neural networks, deep learning, and computational neuroscience, with application to smart manufacturing and healthcare.

Southern University of Science and Technology (SUSTech) is a research-oriented public university founded in Shenzhen, China’s innovation centre. In the Nature Index 2016 Rising Stars rankings, SUSTech was ranked 62nd among the global top 100 institutions with most significant growth in high quality research publications; it ranked as the third fastest growing institution in the world.

Eligibility criteria

Essential:
• A Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, Physics or similar (a First Class or good Upper Second Class Honours degree, or the equivalent from an overseas university);
• Experience in machine learning and data analysis;
• Programming ability in high-level scientific development language, e.g. Python, R, Matlab;
• Strong verbal and written communication skills in English.

Desirable:
• Mathematical maturity with emphasis on estimation and inference;
• Expertise in Bayesian methods or evolutionary computation;
• A Master’s degree with prior publications in leading machine learning and signal processing venues.

IELTS requirements Overall 6.5 minimum, no less than 6 in each category.

How to apply

More information about this studentship and the application procedure can be found in the following website: https://gs.sustech.edu.cn/boshilianpei2020/1727 . 

For informal enquiry, please contact yunpeng.li@surrey.ac.uk or hisao@sustech.edu.cn .


Application deadline

Contact details

Yunpeng Li

yunpeng.li@surrey.ac.uk

(+44)-1483682626

 

Nature-Inspired Computing and Engineering (NICE) group

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