Intern - ML for Computational Fluid Dynamics

About the role

Join Destinus’s world‑leading UAV design team to apply machine learning and numerical optimisation to Computational Fluid Dynamics. You will work at the intersection of the aerodynamics and ML groups, contributing to the design of unmanned vehicles.

Key responsibilities

• Research and develop ML and numerical algorithms to explore the aerodynamic design space.
• Evaluate ideas on real‑world test cases, assess results and present findings.
• Implement and deploy the algorithms within the company’s design pipeline.
• Collaborate with both aerodynamics and ML teams to improve CFD workflows.

Required profile

• Familiarity with Gaussian processes and Bayesian optimisation.
• Hands‑on experience developing Python code in shared repositories (git, code reviews, CI).
• Knowledge of mathematical optimisation concepts such as convex optimisation and non‑linear programming.
• Motivation to push ML boundaries for engineering with minimal supervision.
• Experience in research or CFD simulations is a plus.

Required skills

• Python programming
• Git version control
• Continuous integration workflows
• Gaussian processes
• Bayesian optimisation
• Convex and non‑linear optimisation techniques
• Computational Fluid Dynamics (CFD) basics