KTP Associate

AI/ML Research Engineer, Additive Manufacturing - KTP Associate

The starting salary will be from £33,951 to £38,784 on Grade (E) depending on skill set and experience. 
 
The role:

An exciting opportunity has become available to work on a 36-month Knowledge Transfer Partnership (KTP) between the University of Exeter and Rapid Fusion Ltd. The KTP will develop AI‑enabled software for intelligent process control in Large Format Additive Manufacturing (LFAM), focused on improving polymer deposition consistency and interlayer bonding performance.

The successful candidate will be employed by the University of Exeter and will spend the majority of their time working at Rapid Fusion Ltd in Exeter, with occasional visits to the University of Exeter. They will be expected to work full-time.

Company Information: Rapid Fusion specialises in large-format additive manufacturing systems, including modular 3D printing platforms, AM modules, and robotic AM cells. Their LFAM technology enables the creation of large components with high production outputs, offering a sustainable alternative to traditional manufacturing. More information about the Rapid Fusion Ltd can be found here. 

Qualification / skills we require:

• Educated to first degree level or a good Master’s Degree in Mechanical Engineering, Materials Science, or in a related field of study or equivalent experience. A degree in Computer Science will be considered where supported by relevant experience in materials & manufacturing.
• Strong academic record demonstrating capability in theoretical analysis & practical application.
• Proficiency in Python and/or MATLAB for algorithm development, modelling & data analysis.
• Understanding of polymer materials & processing fundamentals, with familiarity with additive manufacturing processes.
• Knowledge of Finite Element Modelling (FEM) concepts; experience with ABAQUS or similar software desirable.
• Experience with machine learning frameworks (e.g. TensorFlow, PyTorch).
• Knowledge of thermal analysis techniques (e.g. DSC, TGA) beneficial.
• Strong analytical & problem‑solving skills, with ability to interpret complex datasets.
• Excellent written & verbal communication skills, with the ability to explain complex technical concepts to mixed academic & industrial audiences.
• Ability to work effectively within a multidisciplinary academic–industry team, with commercial awareness.
• Experience of managing research projects or contributing significantly to collaborative research.
• Well‑organised, self‑motivated & able to prioritise work independently within a project framework.
• Enthusiasm for hands‑on experimental work alongside computational modelling.
• Adaptable & able to work effectively in a fast‑paced SME environment.
• Understanding of health & safety requirements & good research record‑keeping practices.
• Commitment to equality, diversity & inclusive working practices.
• Willingness to be primarily based at Rapid Fusion Ltd (Exeter), with visits to the University of Exeter as required & flexibility to meet project demands.

Benefits:

• A £6,000 training budget with 10% of your working time dedicated to personal development.
• A unique and challenging career opportunity, working with both industry & academia.
• For the right candidate there will be the opportunity to create an impactful & rewarding career with Rapid Fusion after this project is complete.
• The successful applicant will develop a wide range of industrial & research skills for their future career, utilising the skills & knowledge of company supervisors, as well as benefitting from continuous academic support.
• The opportunity to manage & lead on a project early on in your career.
• Specific KTP residential training.
• The possibility to write academic papers & present at conferences.

Before submitting an application you may wish to discuss the post further by contacting Professor Oana Ghita – o.ghita@exeter.ac.uk at University of Exeter or email Martin Jewell martin.jewell@rapidfusion.co.uk at Rapid Fusion Ltd.

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