Building Information Modelling (BIM) Assistant at Leeds Beckett University
Job Description
Fixed term, part-time – 12 months (0.8 FTE)
The School of Built Environment Engineering and Computing is seeking a Building Information Modelling Assistant for 12 months. This role is integral in delivering an Innovate UK-funded research project built upon a prototype of a Generative AI platform that integrated cost planning with BIM.
Applicants must have an MSc or a PhD in a BIM-related niche, such as 5D BIM, quantity surveying, construction cost engineering, frameworks, documentation, classification, or early warning systems. They are also welcome to bring additional expertise in using AWS/Python/R studio for natural language processing (NLP). Please review the job specifications carefully.
Applicants will have the opportunity to foster a good relationship with members of the Future of Systems, People and Projects (FUPS) lab at the School of Built Environment Engineering and Computing, develop innovative ideas for new proposals, publish from our ongoing research and be encouraged to attend international conferences.
You will join a multidisciplinary consortium comprising academics and industry practitioners to support your role throughout the project. Most of the research activities will be conducted remotely, and you will only be expected to visit the Leeds Beckett University City Campus when required.
For further enquiries about this role, please contact Dr. Temitope Omotayo, t.s.omotayo@leedsbeckett.ac.uk / Tel: +44 (0) 113 812 5249.
Closing date: 18th April 2024 (23:59) Please note that you will not be able to edit or submit a part-completed application form after the closing date.
Interviews will be held during the week commencing April 22nd, 2024.
Working here means you’ll also have access to many benefits, including our generous pension schemes, excellent holiday entitlements, flexible working, reduced study fees, subsidised fitness facilities, and much more.
We welcome applications from all individuals, particularly from black and minority ethnic candidates, as members of these groups are currently under-represented at this post level. All appointments will be based on merit.
