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telecommunications network by integrating innovative fiber-sensing technologies, with the goal of turning the fiber network into an intelligent and pervasive sensor capable of monitoring not only human activities and
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Duration: 3 years Start date: August 2026 at latest The students will be enrolled in the structured PhD programme in the Department of Bioengineering, Imperial College London. https://www.imperial.ac.uk
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). The position is dedicated to the ESA-funded Rover Permittivity Sensor. The expected starting date is February 2025, with an initial contract limited to 2 years and a possible extension. About us: We are strongly
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such as protecting embedded systems from vulnerabilities rooted in sensor physics, studying the impact of physical signals (e.g., acoustics, lasers, electromagnetic emissions) on AI and sensing systems, and
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and real-time data acquisition systems. Participate in testing and deployment of UAV demonstrators at UM6P and OCP sites. Methodology: AI Development: Reinforcement learning, computer vision, and sensor
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analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN implementation topology and its energy efficiency
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of integrated and inertial navigation. The working group deals with multisensor systems, i.e. the sensor fusion of GNSS (GPS, Galileo, GLONASS, Beidou), INS (inertial navigation system), cameras, LiDAR (light
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Brno University of Technology, Central European Institute of Technology | Czech | about 2 months ago
the CEITEC Brno University of Technology is opening a position of a Postdoctoral Research Fellow: “Chemist / Materials Scientist for Development of Biosensors or Sensors based on Single Atom Engineering
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through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software
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. The group Multiomics for Healthcare materials at Empa, St. Gallen generates and integrates multi-modal biomedical datasets with the aim to inform development of new sensors, support nanoparticle-based