Research Assistant in AI and Digital Twin Modelling - Six month fixed term, part-time contract ...

Research Assistant in AI and Digital Twin Modelling - Six month fixed term, part time contract (29.6 hours per week)

Department: Computer Science
Location: Belmont Row (STEAMhouse)
Salary: £38,050 to £44,131 per annum pro rata
Post type: Part time
Release date: 15 May 2026
Closing date: 23:59 BST on Wednesday 03 June 2026
Reference: ABCE26025

Role Summary

We are seeking a Research Assistant in AI and Digital Twin Modelling to join our Department of Computer Science and support the delivery of high quality research and innovation activity across the University. The postholder will play a central role in delivering the core technical components of the DTNet+ funded project over a six month period, focusing on the development of AI enhanced digital twin models to optimise energy efficiency in Positive Energy Districts. The role will involve designing and implementing machine learning and deep learning models, processing and analysing large scale energy datasets, and improving predictive performance for energy demand forecasting, system optimisation and condition/maintenance prediction. Working closely with the Principal Investigator, Dr Syed Attique Shah, the wider research team, and external partners, you will contribute to the development, testing and validation of the digital twin prototype, supporting key project phases including prototype development, performance evaluation and research dissemination.

Key Responsibilities

• Develop and implement AI/ML models for energy demand forecasting and system optimisation
• Support the design and development of the digital twin prototype
• Process and analyse large scale energy datasets (renewable and non renewable)
• Contribute to improving prediction accuracy and system performance metrics
• Assist in testing, validation, and evaluation of the prototype
• Support preparation of technical reports, publications, and conference outputs
• Collaborate with project partners and contribute to research meetings

Qualifications

• A minimum 2:1 undergraduate degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, Software Engineering, Gaming, Computer Vision, or a closely related field
• Strong knowledge of machine learning and deep learning techniques
• Proficiency in Python (TensorFlow, PyTorch, Scikit learn)
• Experience with data analysis, modelling, and predictive analytics
• Understanding of handling large scale, multi source datasets
• Strong problem solving and analytical skills
• Excellent written and verbal communication skills
• Ability to work independently and meet project milestones
• MSc or PhD in AI, Data Science, or related discipline
• Experience with digital twin technologies or simulation systems
• Knowledge of energy systems, smart cities, or IoT data
• Familiarity with reinforcement learning or time series forecasting
• Experience in funded research or industry collaboration projects

Benefits

• Work life balance - Generous leave and hybrid working (role dependent)
• Career development - Opportunities to grow, develop and progress your career
• Reward and wellbeing - Competitive pay, pension, wellbeing support and staff benefits
• Inclusive culture - A supportive, diverse environment where everyone belongs

Equality, Diversity & Inclusion

We are committed to equality, diversity and inclusion. All persons experienced in the job meet the statutory equal opportunity requirements. We will continuously review and improve our policies, practices, and procedures to ensure we promote equality, diversity and inclusion in all aspects of our operations.

Disability Confident Employer

Birmingham City University is proud to be a Disability Confident Employer. We are committed to creating an inclusive and accessible recruitment process and will give disabled applicants who meet the essential criteria for the role a guaranteed interview.

This role does not meet the minimum salary requirements for Skilled Worker visa sponsorship. We are therefore unable to consider applicants who require sponsorship to work in the UK.