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