<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> Your Mission &amp; Challenges<br/><br/><ul><li>Model the Human Experience: Turn multimodal, body-worn data into representations a robot can learn from.</li><li>Bridge Two Bodies: Solve cross-embodiment transfer, translating human motion and interaction into action spaces a robot with a completely different body can use.</li><li>Build Foundation Models That Act: Design pretraining and fine-tuning strategies for robotic foundation models.</li><li>Prove It Works: Build the benchmarks that separate models that merely mimic from models that generalize.</li><li>Shape What Gets Captured Next: Turn model blind spots into sharp, concrete requirements for data capturing devices.</li><li>Cross-Functional Collaboration: Work shoulder to shoulder with hardware and systems engineering teams while staying laser-focused on the data and AI side.<br/><br/></li></ul>What We Can Look Forward To<br/><br/><ul><li>Master's or PhD in Computer Science, Machine Learning, Robotics, or comparable.</li><li>Real, hands-on experience with multimodal foundation models (VLA, video-action, or similar).</li><li>Experience with cross-embodiment transfer, RL based retargeting.</li><li>Deep understanding of low-level robotics control.</li><li>Strong grounding in imitation learning, representation learning, and self-supervised learning across sensor modalities.</li><li>Fluency in modern machine learning frameworks and large-scale training infrastructure.</li><li>A communicator who moves easily between researchers, engineers, and hardware teams.</li><li>Fluent English, German a plus.<br/><br/></li></ul> </div>