Forming AI Development Engineer (KTP Associate)

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.

What you will 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 you have:

• 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 and 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.

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.