Research Assistant or Research Fellow in Software Engineering and Machine Learning

Are you an early-career researcher looking for your first challenge, or are you an experienced researcher looking for your next challenge? Are you passionate about making computers faster and more reliable? Do you have experience in machine learning applications for software performance optimisation and want to join a world-leading research group recognised for its advancements in this field?

You will play a leading role in projects that expand our expertise in machine learning-based code optimisation. You will develop novel techniques that harness the power of machine learning to create optimisation strategies for compilers and memory management libraries for next-generation computing hardware.

We are looking for a candidate with a strong background in computer science, a particular interest in software engineering and low-level systems programming, and a desire to perform cutting-edge research and publish in top conferences and journals.

If you want to be part of a team that is leading ground-breaking research and development in software optimisation, we encourage you to apply. As a member of our team, you will have the chance to collaborate with renowned researchers from other universities and industries worldwide. Additionally, our group maintains strong ties with other prominent companies and research groups, enabling extensive opportunities for career development.

We are open to discussing flexible working arrangements.

To explore the post further or for any queries you may have, please contact: 

Professor Zheng Wang, Professor of Intelligent Software Technology

Tel: +44 (0)113 343 1077 or email: Z.Wang5@leeds.ac.uk 

Please note that due to Home Office visa requirements, this role may only be suitable for first-time Skilled Worker visa applicants if they are eligible for salary concessions. For more information, please visit: www.gov.uk/skilled-worker-visa.

For research and academic posts, we will consider eligibility under the Global Talent visa. For more information, please visit: https://www.gov.uk/global-talent

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Candidate Brief (PDF)

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