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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 40 minutes ago
Materials and Systems is looking for a Postdoc (f/m/d) curvilinear soft materials and structures. Your tasks # Fabricate actuators based on liquid crystal elastomers # Characterize their structural and
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Job Description SDU Robotics , part of the Maersk Mc-Kinney Moller Institute , University of Southern Denmark (SDU), invites applications for one or more 2-year postdoc positions, where
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systems onto real robots for tasks such as tracking, 3D reconstruction, object recognition, and visual SLAM. They will be working with a team composed of PhD students, Research Assistants, and Postdocs
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at the intersection of robot learning, control, and AI for physical systems. The postdoc will work on projects focusing on one or more of the following: Robot Learning & Autonomy – Developing algorithms that allow
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at the intersection of robotics, control & prototyping, and AI/ML. The Postdoc will design, implement, and evaluate robotic systems - including real-time control stacks - and develop learning-enabled perception
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the modularity and the high degree of addressability of self-assembled DNA nanostructures as a biosynthetic tool to probe fundamental aspects of biology. The recruited postdoc will develop two main projects: (1
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. Participation in academic or industrial publications and reports. Profile of the Research Assistant Candidate & Application Materials: Engineering degree or equivalent in Computer Science, Robotics, or Electrical
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for physical systems. The postdoc will work on projects focusing on one or more of the following: Robot Learning & Autonomy – Developing algorithms that allow robots to learn (via exploration or imitation) from
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learning architectures suitable for deployment on resource-constrained robotic systems. The postdoc will have access to state-of-the-art computational resources. Key Responsibilities: Develop novel methods
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-constrained robotic systems. The postdoc will have access to state-of-the-art computational resources. Key Responsibilities: Develop novel methods for robot learning tailored to edge robotics. Validate and test