AI/ML Research Engineer for LFAM Additive Manufacturing

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

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