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Digital Technologies, a joint project focused on sensor systems for movement analysis brings together the OASiS and SyEnsCES teams, located at the École Normale Supérieure de Rennes. Specifically, as part
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TAMU. Experience with machine learning and deep neural network techniques. Experience with wearable and sensors placed in the environment. Knowledge of characteristics associated with mild cognitive
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description AI-enabled polymer monitoring via multi-sensor intelligent non
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Toolkit customization, and performance tuning under hardware constraints; collaborating on robot motion planning, path optimization, and sensor data processing algorithms; implementing and testing ROS nodes
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want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several national and international
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theory, and is expected to have experience with the practical implementation of control algorithms. Who we are Learning and Decision at AAU, founded in 2020, focuses on developing mathematical methods
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principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several national and international research groups, edits one of the major
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influenced corrosion (MIC) in marine environments. It uses AI-supported models, Bayesian data fusion, and real-time sensor data integration. Your responsibilities include: Development of a digital twin (DT
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evaluation of algorithms for: perception in robotics; sensor based control and navigation ; interactive mobile manipulation; multi-sensor data modelling and fusion. This job offer takes place within
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, and sensor data processing algorithms; implementing and testing ROS nodes, embedded controllers, and closed-loop control routines on prototype hardware; preparing technical reports, delivering