Placement
TL;DR
Key Takeaways
- Undertake a 10-week summer placement starting June 2027, developing algorithms for weapon systems.
- Earn £24,460 (pro-rata) with opportunities for paid overtime.
- Gain experience in a hybrid working environment, with 2-3 days on-site per week.
- Must be an undergraduate studying Engineering, Physics, Mathematics, or Computer Science.
About the Role
As an Algorithm Engineer in the Weapons System Algorithms & Performance (WSAP) team, you will develop and optimise algorithms for weapon systems. Your work will impact emerging and future technologies.
What You'll Do
- Develop and optimise algorithms for MBDA's weapon systems.
- Gain visibility into algorithm development, weapon system architecture, performance modelling, and early-stage concepting.
- Work directly with MBDA project teams to deliver critical algorithm components.
- Contribute to projects such as Future Combat Air System (FCAS), STRATUS, and DragonFire.
- Work on areas including routing algorithms, operator decision aids, threat evaluation, multi-weapon co-operation, and machine learning applications.
What We're Looking For
- Current undergraduate working towards a degree in Engineering, Physics, Mathematics, or Computer Science.
- A strong interest in mathematics and applying mathematical techniques to engineering problems.
- Experience in programming for scientific/engineering applications (e.g. MATLAB, Python) would be an advantage.
Placement Details
- Duration: 10-week placement
- Start Date: June 2027
- Working Pattern: Dynamic (hybrid) working: 2-3 days per week on-site.
- Security Clearance: British Citizen or a Dual UK national with British citizenship. Basic Personnel Security Standard (BPSS) checks required.
Benefits
- Salary: £24,460 (pro-rata)
- Annual Leave: 5 days
- Pension: Maximum total (employer and employee) contribution of up to 14%
- Overtime: Opportunity for paid overtime
- Facilities: Subsidised meals, free car parking
- Future Opportunities: Potential to secure a graduate role upon successful placement performance.
