KTP Associate

Exeter; Exeter; Hybrid; GBP 35,000 - 41,000; Full time

Benefits offered by this job

Training budget

Academic support

KTP residential training

opportunities to publish papers

Job summary

University of Exeter seeks a skilled AI/ML Research Engineer for a 36‑month Knowledge Transfer Partnership (KTP) with Rapid Fusion Ltd to develop software for intelligent process control in Large Format Additive Manufacturing. The role blends academic and industrial work, emphasizing polymer science, thermal analysis, and data-driven methods.

The successful candidate will be employed by the University of Exeter, spend most time at Rapid Fusion Ltd in Exeter, and will work full‑time with

Qualifications

• 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 and manufacturing.
• Strong academic record demonstrating capability in theoretical analysis and practical application.
• Proficiency in Python and/or MATLAB for algorithm development, modelling and data analysis.
• Understanding of polymer materials and 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 and problem‑solving skills, with ability to interpret complex datasets.
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts to mixed academic and 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, and able to prioritise work independently within a project framework.
• Enthusiasm for hands‑on experimental work alongside computational modelling.
• Adaptable and able to work effectively in a fast‑paced SME environment.
• Understanding of health and safety requirements and good research record‑keeping practices.
• Commitment to equality, diversity and inclusive working practices.

Responsibilities

• Develop software for intelligent process control in LFAM.
• Work on polymer deposition consistency and interlayer bonding performance.
• Collaborate with academic and industrial partners within a KTP framework.
• Analyse datasets and apply ML/AI techniques where appropriate.
• Engage in hands-on experimental work alongside modelling tasks.

Skills

Python

MATLAB

TensorFlow/PyTorch

FEM concepts

Polymer materials understanding

Data analysis

Strong communication

Education

First degree in Mechanical Engineering

Master’s degree in Materials Science

Computer Science degree considered

Tools

ABAQUS

Job description

About The Role

AI/ML Research Engineer, Additive Manufacturing - KTP Associate

Faculty of Environmental Science and Economy

The starting salary will be from £34,630 to £40,704 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 software for intelligent process control in Large Format Additive Manufacturing (LFAM), focused on improving polymer deposition consistency and interlayer bonding performance. The candidate is expected to have a good understanding of the LFAM process including thermal behaviour of the polymers and knowledge of polymer material science.

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: https://rapidfusion.co.uk/pages/about

Previous applicants to this role need not apply.

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 and manufacturing.
• Strong academic record demonstrating capability in theoretical analysis and practical application.
• Proficiency in Python and/or MATLAB for algorithm development, modelling and data analysis.
• Understanding of polymer materials and 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 and problem‑solving skills, with ability to interpret complex datasets.
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts to mixed academic and 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, and able to prioritise work independently within a project framework.
• Enthusiasm for hands‑on experimental work alongside computational modelling.
• Adaptable and able to work effectively in a fast‑paced SME environment.
• Understanding of health and safety requirements and good research record‑keeping practices.
• Commitment to equality, diversity and inclusive working practices.
• Willingness to be primarily based at Rapid Fusion Ltd (Exeter), with visits to the University of Exeter as required, and 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 and academia.
• For the right candidate there will be the opportunity to create an impactful and rewarding career with Rapid Fusion after this project is complete.
• The successful applicant will develop a wide range of industrial and research skills for their future career, utilising the skills and knowledge of company supervisors, as well as benefitting from continuous academic support.
• The opportunity to manage and lead on a project early on in your career.
• Specific KTP residential training.
• The possibility to write academic papers and present at conferences.

Before submitting an application you may wish to discuss the post further by contacting Professor Oana Ghita – [e-mail] at University of Exeter or email Martin Jewell [e-mail] at Rapid Fusion Ltd.

About Us

Transform Your Career and Help Shape a Greener, Healthier, and Fairer Future

We are committed to understanding different cultures and perspectives, supporting diverse leadership, and striving for social justice. We encourage applications from all groups underrepresented in our community, including racially minoritised individuals and those with disabilities. Our inclusive, merit-based recruitment processes seek to embrace a diverse set of experiences to ensure colleagues feel supported equitably. With over 30,000 students and 7,000 staff from 150 countries, we foster a culture where everyone can thrive.

You can read more about our current accreditations and commitment to Equality, Diversity and Inclusion here, including our commitment to the Armed Forces Covenant.

Why our colleagues love working here

• Flexible working opportunities and leading parental leave initiatives
• Generous annual leave (39-41 days including bank holidays)
• Competitive pension contributions
• A genuine dedication to supporting the health and wellbeing of all colleagues - see initiatives here
• Sustainability and the environment being at the heart of what we do
• A £4,000 training budget with 10% of your working time dedicated to personal development
• A unique and challenging career opportunity, working with both industry and academia
• You will develop a wide range of industrial and research skills for their future career, utilising the skills and knowledge of company supervisors, as well as benefitting from continuous academic support
• The opportunity to manage and lead on a project early on in your career
• Specific KTP residential training
• The possibility to write academic papers and present at conferences

How we can help

If you're considering applying and need support to do so, please get in touch with us at [e-mail]. You can request reasonable adjustments within your application or by contacting us. You can also choose to be considered under our Disability Confident Scheme and find out here how this is managed during our recruitment and onboarding process.