ABOUT THE ROLE
Help develop the Python tools behind early aircraft design decisions. You will build on ERC’s existing multi-objective design optimisation framework, extending its functionality and improving the engineering models used in initial aircraft sizing.
A central part of your work is capturing the physical effects and design dependencies that matter early in development, and translating findings from higher-fidelity analyses, supplier data and testing into efficient models for sizing loops and optimisation studies. This helps ERC make better-informed design decisions early on.
WHAT YOU WILL DO
Develop Python functionality for aircraft sizing, design exploration and multi-objective optimisation
Add and improve models for performance, aerodynamics, propulsion, energy and mass with the relevant engineers
Capture the physical relationships, constraints and interactions that drive early design decisions at sizing-level detail
Build and validate surrogate models based on higher-fidelity simulation results and engineering data
Support trade studies by comparing aircraft concepts, investigating sensitivities and weighing competing design objectives
Strengthen modularity, interfaces, documentation and testing so the framework stays reliable and easy to extend
Create plots and summaries that help engineers interpret results, recognise model limitations and identify infeasible designs
WHAT YOU BRING
Current studies in aerospace or mechanical engineering, computer science, applied mathematics or a related discipline
Practical Python experience and an interest in scientific computing
An interest in aircraft design and the physics behind computational models
Familiarity with numerical methods, data analysis or optimisation
The habit of questioning assumptions, checking units and physical plausibility, and documenting model limitations
A hands-on, self-reliant approach and the initiative to investigate problems and see them through
Enjoyment of collaborating with engineers, sharing progress and seeking input when needed
Moreover, it would be helpful if you alsohave worked with NumPy, SciPy, pandas or similar libraries
have experience with Git and automated testing
bring some exposure to surrogate modelling or multi-objective optimisation
WHAT WE OFFER
Full-scale aerospace engineering, not concept slides
A 60+ engineer team at Ottobrunn
Real ownership and flat hierarchies: a modern startup culture where your input shapes decisions, not just execution
Flexible working hours, remote work, and competitive compensation
Health & wellbeing: EGYM Wellpass membership and subsidized lunch in our canteen
Office extras: espresso coffee, fresh fruit, and soft drinks, plus regular team and company events, and plenty more once you're on board