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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 2 months ago
– Intelligent Robotic Endoscopes for Improved Healthcare Services (Call HORIZON-CL4-2023-DIGITAL-EMERGING-01-01). Inria (DEFROST team) is partner No. 3 of the consortium, coordinated by the University
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assistant requires a master’s degree and the position as postdoc requires a PhD degree. In both cases an educational background within robotics, mechanical engineering, electrical engineering, computer
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excellence in both fundamental and applied research, spanning fields such as neuroscience and cognition, humanoid technologies and robotics, artificial intelligence, nanotechnology, and material sciences
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information about our research group can be found at: https://autonomousrobots.nl/ Job requirements We are looking for a candidate with: A PhD degree in Robotics, Control, Aerospace Engineering, Mechanical
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the hardware that enables the next generation of intelligent robots to physically sense and interact with their environment. Job requirements You hold a PhD in Electrical Engineering, Microelectronics
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PhD in biology, cognitive sciences, computational neuroscience, bioinformatics, robotics, or a related field Strong expertise in computational data analysis (e.g., behavioral analysis, signal processing
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, Python, Robot Operating System) is required. The position is open to PhDs with backgrounds in AI, and/or computer vision and robotics/controls, and with less than 5 years of experience after receiving
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computational methods for the control, optimization, and coordination of complex dynamical systems. The work will emphasize applications to multi-agent systems, including robotics, autonomous systems, and
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As part of an ambitious collaborative research project between the Sint Maartens Kliniek and the University of Twente’s Wearable Robotics Lab, we are seeking a highly motivated postdoctoral
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About the role The postdoctoral researcher will work on a project funded by Amazon Robotics that aims to improve decision-making in large mobile-robot fleets through learning-based corrections