Junior Materials Data Scientist

Lucideon group limited; Stone; On-site; GBP 38,000 - 58,000; Full time

Job summary

Lucideon is seeking a Materials Scientist – Data Development on-site in Stone to bridge materials science with data analytics, modelling and machine learning. You will extract insights from experimental and historical datasets to drive materials development, process optimisation and performance improvements across aerospace, healthcare, energy and manufacturing.

You will collaborate with cross-disciplinary teams, collect and analyse data from testing and development activities, and apply ML

Qualifications

• Degree in Materials Science or a closely related field.
• Experience applying data analysis to materials science problems.
• Ability to interpret experimental data and build predictive insights.
• Clear communication and collaboration within multi-disciplinary teams.

Responsibilities

• Collaborate with materials scientists, engineers and data specialists to solve technical challenges using data-driven approaches.
• Collect, analyse and interpret data from materials testing, characterisation and development activities.
• Apply data analytics, machine learning and computational modelling tools to identify insights and support materials innovation.
• Develop, validate and refine predictive models for materials design, process optimisation and performance improvement.
• Communicate technical findings through reports, data visualisations and presentations to a range of audiences.
• Keep up to date with emerging developments in materials informatics, data science and machine learning.

Skills

Data analysis

Machine learning basics

Teamwork

Education

BSc in Materials Science

MSc in Materials Science

Tools

Python

R

COMSOL Multiphysics

Job description

Are you passionate about materials science and excited by the potential of data to transform how materials are designed, developed and optimised?

At Lucideon, we’re looking for a Materials Scientist – Data Development to join our growing team. This is a unique opportunity to combine materials science expertise with data analysis, modelling and emerging machine learning techniques to solve real‑world challenges across sectors including aerospace, healthcare, energy and advanced manufacturing.

Based on site in our state of the art facilities in Stone, Staffordshire, you’ll be working in a cutting‑edge materials innovation environment, collaborating with materials scientists, engineers and data specialists to extract insights from experimental and historical datasets, helping to drive next‑generation materials development, process optimisation and performance improvement. This role offers the chance to work at the forefront of materials science and data‑driven innovation, while developing new skills, contributing to high‑impact commercial projects and building a career in this rapidly evolving field.

What You'll Be Doing

• Collaborate with materials scientists, engineers and data specialists to solve technical challenges using data‑driven approaches.
• Collect, analyse and interpret data from materials testing, characterisation and development activities.
• Apply data analytics, machine learning and computational modelling tools to identify insights and support materials innovation.
• Develop, validate and refine predictive models for materials design, process optimisation and performance improvement.
• Communicate technical findings through reports, data visualisations and presentations to a range of audiences.
• Keep up to date with emerging developments in materials informatics, data science and machine learning.

Essential Requirements

• BSc or MSc in Materials Science or a related discipline.
• Demonstrable experience in materials science gained through industry, research, academia or a similar environment.
• Knowledge of materials characterisation and analytical techniques such as: SEM, TGA, Rheology / Powder Rheology, DMTA, Mechanical testing methods.
• Understanding of data analysis principles.
• Strong analytical and problem‑solving skills.
• Excellent communication and teamwork abilities.
• A passion for innovation and continuous learning.
• Applicants must be eligible to obtain and maintain UK Security Check (SC) clearance. Please note that security clearance eligibility may be subject to UK Government nationality and residency requirements.

Desirable Person Requirements

• Experience applying machine learning techniques to scientific or engineering datasets.
• Knowledge of Python or R for data analysis.
• Familiarity with libraries such as: Scikit‑learn, NumPy, TensorFlow, PyTorch.
• Experience with computational modelling or a willingness to learn tools such as COMSOL Multiphysics.
• Knowledge of advanced ceramics and their applications.
• Experience working within an agile project environment.

Apply today and help shape the future of materials innovation through data‑driven science!