Your Mission & Challenges
•
Model the Human Experience: Turn multimodal, body-worn data into representations a robot can learn from.
•
Bridge Two Bodies: Solve cross-embodiment transfer, translating human motion and interaction into action spaces a robot with a completely different body can use.
•
Build Foundation Models That Act: Design pretraining and fine-tuning strategies for robotic foundation models.
•
Prove It Works: Build the benchmarks that separate models that merely mimic from models that generalize.
•
Shape What Gets Captured Next: Turn model blind spots into sharp, concrete requirements for data capturing devices.
•
Cross-Functional Collaboration: Work shoulder to shoulder with hardware and systems engineering teams while staying laser-focused on the data and AI side.
What We Can Look Forward To
•
Master's or PhD in Computer Science, Machine Learning, Robotics, or comparable.
•
Real, hands-on experience with multimodal foundation models (VLA, video-action, or similar).
•
Experience with cross-embodiment transfer, RL based retargeting.
•
Deep understanding of low-level robotics control.
•
Strong grounding in imitation learning, representation learning, and self-supervised learning across sensor modalities.
•
Fluency in modern machine learning frameworks and large-scale training infrastructure.
•
A communicator who moves easily between researchers, engineers, and hardware teams.
•
Fluent English, German a plus.
