Research Assistant / Research Fellow - 16192

Brunel University of London; Uxbridge; Hybrid; GBP 41,000 - 49,000; Full time

Benefits offered by this job

Hybrid working

Generous annual leave

Pension scheme

Professional development

Job summary

Brunel University of London, Uxbridge Campus, invites applications for a Research Assistant / Research Fellow (Ref 16192) in the Department of Computer Science. The role contributes to EU/UK projects on a wireless network digital twin system for smart city logistics, with ML-based algorithms and 5G/6G evaluation.

Full-time, fixed-term to 31 March 2027, with London Weighting included; hybrid working arrangements.

Qualifications

• Knowledge in machine learning, large AI models, LLMs and AI-generated content (AIGC) is preferred.
• Publications in leading AI/ML conferences are advantageous.

Responsibilities

• Contribute to EU/UK projects developing a wireless network digital twin for smart city logistics.
• Perform performance analysis for 5G/6G systems and develop ML-based algorithms.

Skills

Machine learning

Large AI models

LLM

AIGC

Publications in AI/ML conferences

Job description

Brunel University of London was established in 1966 and is a leading multidisciplinary research-intensive technology university delivering economic, social and cultural benefits. For more information please visit: https://www.brunel.ac.uk/about/our-history/home

College / Directorate

College of Engineering, Design & Physical Sciences

Department

Department of Computer Science

Full Time / Part Time

Full Time

Posted Date

03/08/2026

Closing Date

24/09/2026

Ref No

5190

Documents

• Research Assistant - Job Description (Word , 120.02kb)
• Research Fellow - Job Description (Word , 116.4kb)

Position Title: Research Assistant / Research Fellow – 16192

College/Department: College of Engineering, Design and Physical Sciences / Department of Computer Sciences

Location: Brunel University of London, Uxbridge Campus

Salary

Salary for Research Assistant: R1 Grade from: £37,118 to £39,144 per annum inclusive of London Weighting with potential to progress to £40,202 per annum inclusive of London Weighting through sustained exceptional contribution. (Pro-rata for Part-time)

Salary for Research Fellow: R1 Grade from: £41,292 to £44,762 per annum inclusive of London Weighting with potential to progress to £48,557 per annum inclusive of London Weighting through sustained exceptional contribution. (Pro-rata for Part-time)

Hours: Full-time

Contract Type: Fixed term until 31 March 2027

Brunel University of London was established in 1966 and is a leading multidisciplinary research-intensive technology university delivering economic, social and cultural benefits. For more information please visit: https://www.brunel.ac.uk/about/our-history/home

The Department of Computer Science at Brunel where this project will be conducted is ranked 3rd in the UK (2020-22) overall in the NTU Performance Ranking of Scientific Papers for World Universities and, for five years in succession, 1st in the UK for H-index and Highly Cited Papers (2018-2022). According to 2023 Shanghai Academic Ranking of World Universities (ARWU), Computer Science & Engineering at Brunel has been ranked 7th in the UK and a very respectable 101-150 position worldwide. Moreover, according to the 2023 Times Higher Education rankings, Computer Science is 17th in the UK and in the Top 200 worldwide.

The successful candidate will contribute to the EU/UK projects (with funding support from Innovate UK, EU and UKRI) which aim to develop a wireless network digital twin system for smart city logistics and last-mile applications. It includes performance analysis for 5G/6G systems, developing machine learning-based algorithms, establishing a radio propagation model, and conducting network planning and optimisation. The successful candidate will also need to visit our industrial partner in the UK/EU, to do collaborative research and experiment. The candidate with the following knowledge is preferable: machine learning, large AI model, large language model (LLM), and Artificial intelligence generated content (AIGC). Preference will also be given to candidates with publications in leading AI/ML conferences.

We offer a generous annual leave package plus discretionary University closure days, excellent training and development opportunities as well as a great occupational pension scheme and a range of health-related support. The University is committed to a hybrid working approach.

Brunel University London is fully committed to creating and sustaining a fully inclusive workforce culture. We welcome applicants from all backgrounds and communities, we particularly welcome applicants who are currently under- represented in our workforce.