Research Assistant at Brunel University

Brunel University; Greater London; On-site; GBP 37,000 - 39,000; Part time

Job summary

Brunel University London seeks a part-time Research Assistant to support the Lean Optimal feasibility study within the Digital Manufacturing Research Centre. The role focuses on developing AI-assisted predictive modelling using data from SMEs, with a view to creating actionable guidance without disrupting production.

The position runs for six months at 25.31 hours per week, with a salary that reflects London weighting for a Grade R1 level, pro-rated for part-time work.

Qualifications

• Background in Electronics, Computer Science, Applied Mathematics or Manufacturing Systems with ML-Data Analytics orientation.
• Experience in R&D or industrial settings supporting design and development of data acquisition, analytics and predictive modelling.

Responsibilities

• Join Brunel Digital Manufacturing Research Centre, Department of Engineering, College of Engineering, Design and Physical Sciences.
• Support Lean Optimal feasibility study to determine if predictive insights and recommendations can be generated within SME environments.
• Code the solution into an integrated software application and contribute to a peer-reviewed publication.

Skills

Data analytics

Machine Learning

AI modelling

Software development

Education

Electronics

Computer Science

Applied Mathematics

Manufacturing Systems

Tools

Predictive modelling

Job description

Position Summary

Apply for Research Assistant at Brunel University in London, ENG, GB. This Full time on site position offers great opportunities for career growth.

Key Details

• College / Directorate College of Engineering, Design \& Physical Sciences Full Time / Part Time Part Time
• Posted Date 04/09/2026
• Closing Date 01/10/2026
• Ref No 5211
• Location: Brunel University London, Uxbridge Campus
• Salary: Grade R1 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)
• Hours: Part-time at 25.31 hours per week
• Contract Type: Fixed-term for 6 months

Key Responsibilities

• Candidate will join the Brunel Digital Manufacturing Research Centre, Department of Engineering, College of Engineering, Design and Physical Sciences at Brunel University.
• SME manufacturers lose between 2% and 5% of output through scrap and rework, driving unnecessary material consumption, machine hours, and energy use.
• The Lean Optimal feasibility study will investigate whether a simple, affordable and scalable predictive system can help SMEs identify this drift by making use of the production data they already collect.
• The project explores an approach that combines lightweight AI-assisted modelling, drift detection and basic self-learning behaviour with operator guidance.
• The aim is not to build a full system but to establish whether predictive insight, early warnings and actionable recommendations can be generated within the constraints of real SME environments.
• This includes assessing data readiness, understanding operational workflows and determining how predictions and guidance can be presented in a form that supports decision making without disrupting production.
• The concept builds on earlier research from the Factory of the Future programme, where predictive modelling, integrated information systems and automated warning mechanisms formed the basis of the Lean Optimal philosophy.
• The candidate will have at least 5 years of experience working in R&D and/or industrial set up to support the design and development of advanced data acquisition, analytics and predictive modelling using novel AI and Machine Learning techniques for optimising manufacturing processes with lean objectives.
• This highly applied short-term research project requires highly skilled individuals requiring minimum time to utilise their capabilities to think innovatively and produce solutions that will be applied and tested in limited amount of time with demonstrable output (in the form of software application and 1 peer reviewed publication).
• The educational background should be in areas such as Electronics, Computer Science, Applied Mathematics, Manufacturing Systems with Machine Learning-Data Analytics orientation.
• This six months period is to assist the existing research team to finalise the models and code the solution into a software application.
• The nominee should be expert in these areas and type of projects.
• The candidate main role is to support the existing SERG members with further testing and validation of models as well as coding the solutions into an integrated software application.
• Post Profile This position requires strong computation and software development, mathematical and analytical skills supported by evidence of your previous activities and responsibilities
• Technical and engineering skills to develop a concept, apply the design methodologies, implementation, testing, validation and verification
• Strong Communication and Writing Skills to write scientific and technical reports.
• Management of Staff and Students To provide appropriate advice to staff and students on their research area or research methodologies
• Effective Behaviours Timeliness Meeting Deadlines Communication and Networking Networking group across colleges Ability to negotiate and influence Ability to plan and organise own workload Ability to adapt to a flexible approach to the demands of a busy college/department in order to accommodate changes in priorities when required

Equality, Diversity and Inclusion

Brunel University London has a strong commitment to equality, diversity and inclusion.

Closing Date

Closing date: 1 October 2026