Working Student- Ecodesign

Job description

Here at The Exploration Company, we are developing, producing, and operating Nyx, a modular and reusable space orbital vehicle that can eventually be refuelled in orbit and that can carry cargo - and potentially humans in the longer run. We are looking for a motivated working student to join us as a Working Student- Ecodesign to help in our LCA tools. Tasks As our Ecodesign Working Student, your role will evolve alongside our projects and ambitions. On a day-to-day basis, you'll be: Improving and expanding our internal Life Cycle Assessment (LCA) tools, refactoring Python scripts to make them more robust, modular, and easier to build on over time. Supporting the integration of AI agents into our Ecodesign and LCA workflows. Keeping our scripts and data pipelines up to date with the latest LCA standards, so that results are traceable, reproducible, and hold up to scrutiny. Running Life Cycle Assessments on actual projects, products, and components in development at The Exploration Company. Identifying where our environmental footprint is largest, across materials, manufacturing, operations, and end-of-life, and flagging where improvements are possible. Quantifying the environmental impact of design decisions, comparing scenarios, and presenting trade-offs with clear assumptions and sensitivity checks. Contributing to how we develop and document LCA methodologies internally, so that others across the company can run consistent, reliable assessments. Presenting your findings to both technical and non-technical colleagues, and translating what the numbers mean into concrete, actionable recommendations. Qualifications & Background Bachelor's or Master's student in Computer Science, Engineering, Environmental Science, Sustainability, or a related field, with a solid technical foundation. Good Python skills and a strong interest in writing code that's clean, well-documented, and maintainable. Some familiarity with Life Cycle Assessment and Ecodesign, or a genuine willingness to dive into it quickly. Prior experience, hands-on or academic, with LCA tools or sustainability methodologies is a plus. A background in material science, space systems engineering, or product design is welcome. Knowledge of AI or machine learning is a strong bonus, particularly if you're keen to apply it to LCA data challenges. Skills & Behaviours Comfortable working independently as well a…