"Forming AI Development Engineer (KTP Associate)"

The role

The University of Bristol wishes to recruit a highly skilled & qualified graduate / post-graduate to lead and deliver a Knowledge Transfer Partnership (KTP) with iCOMAT Limited, a composites parts and pre-formed supplier to the aerospace, defence, automotive and space sectors. The post holder will be based at iCOMAT in Gloucester and will develop a simulation modelling process for forming composite fibres into 3D-shaped component parts.

High quality numerical analysis is a crucial part of the process of understanding and predicting high quality manufacture of composite structures. However, these tools have historically suffered from high computational costs preventing their large-scale use in an industrial environment. The role holder will develop and deploy theory-guided machine learning tools for the prediction of composite manufacturing processes. You will work on development of algorithms, custom written codes, application of commercial finite element software and development of user subroutines, and embedding these into iCOMAT’s processes.

This 24-month KTP includes a £4,000 training budget with 10% of your time dedicated to your personal development. You will have access to a pension scheme with generous employer contributions. This unique funded opportunity from Innovate UK provides a blend of training and expert supervision, focusing on fast-track development of personal, organisational, leadership and analysis skills. The project will deliver new cutting-edge technology, provide excellent career development and hone your skills to become a future leader.

What will you be doing?

• The project will develop a new simulation modelling process for forming composite fibres into 3D-shaped component parts.
• Development, application and support of hi-fidelity finite element tools, bespoke codes and theory-guided machine learning algorithms for the prediction of manufacturing processes in composite materials.
• Development of user subroutines for finite element constitutive models
• Validation of model and numerical analysis results
• You will be the project lead, managing your own workload and ensuring outputs, including leading on meetings and workshops.
• Direct problem-solving activities and your own learning.
• You’ll have creative freedom to suggest changes and develop the project plan.

You should apply if

• First degree in Engineering, Applied Mathematics or Physics (with an MSc or PhD in a related topic).
• Experience of processing of numerical and/or experimental data & systems thinking.
• Excellent communication skills and experience of developing research projects or industry/academia collaborations.
• Willingness to lead and take ownership of the project with excellent problem-solving skills.
• Knowledge of data science/AI frameworks is desirable.
• Experience or awareness of coding (e.g. Python , Fortran or C++) is desirable.

Additional information

For internal queries, please contact:

Prof in Composite Structures Stephen Hallett (Stephen.Hallett@bristol.ac.uk) or

Dr Jonathan Belnoue, Senior Lecturer  (Jonathan.Belnoue@bristol.ac.uk).

To find out more about what it's like to work in the Faculty of Engineering, and how the Faculty supports people to achieve their potential, please see our staff blog:

https://engineering.blogs.bristol.ac.uk/category/engineering-includes-me/

Contract type: Open ended with fixed funding for 24 months

Work pattern: Full-time/TBC

This advert will close at 23:59 UK time on 23/11/2025

Interviews are anticipated to take place after the closing date in November 2025

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The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, & retain individuals with different experiences, backgrounds & perspectives,