Computational Materials Modeller - Year in Industry Placement

Tussell Limited; Aldermaston; On-site; GBP 18,000 - 24,000; Full time

Job summary

AWE invites you to join a placement year focused on computational modelling of advanced materials. You'll work with materials and analytical scientists to develop and test models that predict ageing and reliability.

You will gain hands-on experience across the full modelling lifecycle, including coding in MATLAB and OpenFOAM, data analysis, optimisation, and validation, within an office and laboratory environment at Aldermaston.

Qualifications

• Must be working towards at least a 2:2 degree in Mathematics, Physics, CS, Materials Science or Chemistry.
• Clear maths and programming skills with willingness to learn.
• UK national with DV clearance eligibility (security requirements).

Responsibilities

• Model development with scientists to understand material ageing and trends.
• Analyse experimental data with statistical techniques to extract insights.
• Write and run code using MATLAB, Mathematica, OpenFOAM and R.
• Test and optimise parameters; verify models against test cases.

Skills

Mathematical thinking

Programming confidence

Data analysis

Collaboration

Education

2:2 degree

Tools

MATLAB

Mathematica

OpenFOAM

R

Job description

Use computational modelling to help predict how complex materials behave. You'll develop and test models that help scientists understand material performance, ageing and reliability, supporting AWE's mission-critical work.

What you could work on

• Model development: Work with materials and analytical scientists to understand material ageing and propose ways to model observed trends.
• Data analysis: Use statistical techniques to analyse experimental data and turn results into useful insight.
• Coding: Write, develop and run code using tools or languages such as MATLAB, Mathematica, OpenFOAM and R.
• Testing and optimisation: Use computational techniques to optimise parameters, then verify and validate models against suitable test cases.

Why being onsite will support your development

This is an office-based placement. Due to the nature and security of our work, we cannot guarantee opportunities to work from home for part of the week. Being onsite means you'll learn directly from subject matter experts, access hands-on support and build connections across technical teams. This day-to-day access can accelerate your development and help you get more from your placement year.

Where this placement could take you

You'll gain practical experience across the full model-development lifecycle, including coding, statistical analysis, optimisation, verification and validation. The placement can prepare you for careers in computational modelling, data science, scientific software, materials modelling or related technical fields, with the potential to return to AWE through a future graduate opportunity.

Working pattern

A 9-day working fortnight, with every second Friday off. This is an office and laboratory-based role at Aldermaston, near Reading. Due to the nature and security of the work, we cannot guarantee opportunities to work from home.

You should be working towards

You should be working towards at least a 2:2 degree in Mathematics, Physics, Computer Science, Materials Science or Chemistry. Mathematics students should have modelling experience, while Chemistry students should be able to demonstrate strong maths or programming skills. You must be graduating in either 2029 or 2030. You must be a UK national, hold a UK passport, have lived in the UK for the past 10 years and be willing and able to obtain and maintain DV security clearance.

The key skills we're looking for

• Mathematical thinking: You enjoy turning real-world problems into logical, structured approaches.
• Programming confidence: You're interested in developing code and using computational tools to solve technical challenges.
• Data analysis: You can explore data, identify patterns and explain what the results mean.
• Collaboration: You can learn from specialists, share ideas and contribute positively to a multidisciplinary team.