Who We Are: We are a rapidly growing embodied AI company revolutionizing human labor. Leveraging cutting-edge robotics and advanced artificial intelligence, we develop transformative technologies that redefine how work is done across multiple industries—empowering businesses to streamline operations, boost productivity, and unlock new possibilities. Overview: We are offering a thesis position focused on developing reactive, zero-shot, model-free robotic suction grasping techniques. The research aims to enable robots to generalize to unseen objects without prior training, leveraging closed-loop control and real-time feedback mechanisms. Research Objectives: Develop zero-shot suction grasping policies using multimodal feedback (vision, depth, force). Design and evaluate closed-loop control architectures for real-time reactive manipulation. Investigate model-free reinforcement learning and visual-language models for generalization to unseen objects. Validate methods on industrial-grade robotic systems and contribute to open-source research publications. Qualifications: Master’s degree in Robotics, Machine Learning, Mechanical Engineering, or a related field. Strong background in control systems, reinforcement learning, or robotic manipulation. Experience with robot control frameworks (e.g., ROS) and hardware integration. Solid programming skills (Python, C++) and familiarity with deep learning frameworks. Strong analytical and research skills with a proven publication record being a plus. What We Offer: Free meals at the workplace Flexible working hours Option to work from home when needed A motivated team and an open corporate culture