Enrolled MSc student in Machine Learning, Computer Science, or Robotics — with a research mindset and the discipline to support it with rigorous, reproducible evaluation
Strong PyTorch skills; hands-on RL experience using Stable Baselines3, Isaac Lab, or similar frameworks — you've trained policies and analysed why they fail, not just run examples
You've integrated ML inference pipelines with ROS2 — or are confident you can make it work cleanly in a real-time control context
Experience with foundation model fine-tuning is a strong plus — this work involves adapting large models for a specific purpose, not just deploying them off the shelf
You're interested in safety-critical AI — not as a compliance checkbox, but as a genuinely hard technical and methodological problem
Strong mathematical foundation across linear algebra, optimisation, and probability — you're comfortable with the theory behind what you implement
