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Field
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data, and sensor data such as CGM measurements (continuous glucose monitoring), activity trackers, and other wearable sensors. Contribute to grant proposals and projects for national and international
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-efficient digital AI/ML accelerator for real-time transmitter error correction in high-speed RF systems. Co-design and validate on real silicon. Job description Wireless networks are becoming increasingly
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contribute to research on secure and efficient AI for embedded cyber-physical power electronic systems. The main activities include: Analyzing how disturbances or cyberattacks, such as sensor manipulation
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radiation detectors (leader: Prof. Masayuki Wada); Electronics, seismic and environmental sensors (leader: Dr. Mariusz Suchenek). Astrocent is formally an administrative division of Nicolaus Copernicus
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disturbances or cyberattacks, such as sensor manipulation, electromagnetic interference, or injected faults, can affect the behaviour of power electronic systems. Developing data-driven models that capture how
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, transportation networks, and water treatment plants, increasingly rely on AI-driven decision-making for efficiency and autonomy. However, these systems face unique safety challenges. Real-world conditions
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materials in the area of acoustic sensor and actuator technology Collaboration in an interdisciplinary research team with external and internal partners Your qualifications: A university degree (master's or
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, Mesoscopic Physics/Nanoscience , Metrology , MOTRIMS , Multi-messenger Astronomy , Nano- and Optomechanis , Nanomechanics , Nanoscience , Nanotechnology , Network , Networks , Neutrino Astronomy , Neutrino
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, CVPR, ECCV, PR, or PRL. Experience in leading and coordinating research projects. Experience in biometric data acquisition, sensor calibration, and dataset management. Expertise in deep learning, GenAI
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Optimization group within the Delft Institute of Applied Mathematics at TU Delft is offering a full-time PhD position in the area of mathematical phylogenetics. Phylogenetic networks are directed acyclic graphs