14 cognition research jobs at Delft University of Technology (TU Delft) in Netherlands
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Requirements Need to have: Experience with radiative transfer algorithms including polarisation Experience with the development of large codes Knowledge of scattering and absorption processes in planetary
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knowledge in software integration methods. Knowledge in machine learning and deep learning methods. Knowledge in OpenCV, ROS, and Gazebo. Well organized and excellent time management skills. Excellent command
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knowledge in software integration methods. Knowledge in machine learning and deep learning methods. Knowledge in OpenCV, ROS, and Gazebo. Well organized and excellent time management skills. Excellent command
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adaptation, etc. We are looking for a candidate with strong computer science background and system thinking. The knowledge and experience in the energy field is highly desirable. The affinity with modeling and
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, literature and best practices; (3) testing these activities and investigating how transdisciplinary skills may develop in practice and create a knowledge base on how various skills could be taught; (4) inform
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Dr. Yasemin Vardar at the Human-Robot Interaction Section of the Cognitive Robotics Department of the Delft University of Technology. Our overarching goal is to understand the relationship between
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will be supervised by Dr. Georgios Papaioannou (Intelligent Vehicles Section at Cognitive Robotics Department ) and Dr. Meichen Guo (Delft Center for Systems and Control). The project is funded as
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Engineering or a related field. Expert knowledge of railway dynamics and vibration and experience in finite element modelling, testing, measurement and signal processing are required. You should have a high
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disseminate your findings and knowledge in relevant communities. Your research is part of a multi-disciplinary drive towards stable, reliable sustainable energy systems. Which is why you’ll work closely with
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adaptation, etc. We are looking for a candidate with strong computer science background and system thinking. The knowledge and experience in the energy field is highly desirable. The affinity with modeling and