Applied & Theoretical Scientist - Year in Industry Placement

Tussell Limited; Aldermaston; On-site; GBP 21,000 - 27,000; Full time

Job summary

Tussell Limited in Aldermaston invites you to a placement year where you’ll apply physics, mathematics and computation to solve complex scientific problems and support mission‑critical technologies. You’ll work on radiation science, physics modelling, extreme materials and algorithms, gaining hands‑on experience in modelling, measurement and data analysis.

This office and laboratory‑based role is 9‑day fortnights with every second Friday off; you must be graduating in 2029 or 2030 and be a UK

Qualifications

• Working towards at least a 2:2 degree in Physics, Mathematics, Data Science, Structural Engineering or Computer Science.
• UK nationality with DV clearance eligibility.
• Strong analytical thinking and ability to communicate in a small team.

Responsibilities

• Radiation science: Support radiation detection, measurement and analysis using experimental and computational approaches.
• Physics modelling: Explore photon, electron or neutron behaviour using modelling codes such as MCNP.
• Extreme materials: Simulate or measure material properties in unusual states, including conditions found inside stars and planets.
• Algorithms and assessment: Develop computational algorithms and apply complex mathematical assessment to real physics problems.

Skills

Analytical thinking

Mathematical confidence

Computational curiosity

Collaboration

Education

2:2 degree in Physics, Mathematics, Data Science, Structural Engineering or Computer Science

Job description

Use physics, mathematics and computation to solve complex scientific problems. You’ll apply scientific theory, modelling and measurement to help understand complex physical systems and support the lifecycle of mission‑critical technologies.

What you could work on

• Radiation science: Support radiation detection, measurement and analysis using experimental and computational approaches.
• Physics modelling: Explore photon, electron or neutron behaviour using modelling codes such as MCNP.
• Extreme materials: Simulate or measure material properties in unusual states, including conditions found inside stars and planets.
• Algorithms and assessment: Develop computational algorithms and apply complex mathematical assessment to real physics problems.

Why being onsite will support your development

This is an office, laboratory and site‑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 in scientific modelling, measurement, data analysis, computational methods and technical problem‑solving. The placement can prepare you for careers in applied physics, theoretical physics, scientific computing, modelling, data science 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 at least a 2:2 degree in Physics, Mathematics, Data Science, Structural Engineering or Computer Science.

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

• Analytical thinking: You enjoy breaking complex scientific problems into clear, logical steps.
• Mathematical confidence: You can apply quantitative methods and use evidence to explore technical questions.
• Computational curiosity: You’re interested in modelling, coding or using digital tools to test scientific ideas.
• Collaboration: You can learn from specialists, communicate your thinking and contribute positively to a small team.