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this project, you will combine a deep knowledge of physical chemistry with robotic systems and AI models. You will learn how to programme advanced robotic systems and how to implement aspects of deep learning
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demonstrate it in simple robots. Our work bridges organic neural systems and hysteron computing, and leverages (bio)chemical and electrical feedback to materialize adaptivity and plasticity. Key questions
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nearly every facet of our life, including healthcare, education, mobility, AI, robotics and culture. The positions: PhD candidate / project 10 focuses on understanding the effects of lighting on, in and
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of Supervisory Controller Synthesis. Affinity with application domains within mechanical engineering such as, e.g., mechatronics or robotics. Strong analytical and problem-solving skills, with a passion for
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robotic systems and AI models. You will learn how to programme advanced robotic systems and how to implement aspects of deep learning and neural networks for chemical property prediction. You will be part
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behavior, thereby affecting nearly every facet of our life, including healthcare, education, mobility, AI, robotics and culture. The positions: PhD candidate / project 10 focuses on understanding the effects
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under varying lighting, fabric blends, and soiling; (5) porting the inference pipeline to an embedded/edge-compute platform; (6) integrating with our robotic pick-and-place cell for iterative field trials
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environment with cutting-edge laboratories and facilities to support transformative research across mechanical, materials and robotics engineering; optimisation, systems and control; and sustainable chemical