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-house database of experimental real-world data enabling large-scale validation of developed algorithms. Wind turbine drivetrains are critical components, and their failures can lead to significant
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, or their LiDAR beam is blocked by a truck. To reach level-4/5 autonomy, we need teamwork: nearby vehicles, drones, and roadside units must co-perceive their environment, sharing and fusing complementary sensor
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detailed local inspection. Digital twin simulations: Developing simulation environments replicating sensor characteristics and anomaly conditions to test perception algorithms under controlled, repeatable
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water, etc.) by fusing sensor data (e.g. sonar, INS, USBL). Collaborative control strategies: Developing coordinated control algorithms that allow the USV and UUV to perform joint missions without
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PhD position on Closed-loop testing for faster and better EM evaluation of complex high-tech systems
with antennas, evaluate different algorithms for EM field strength data, investigating the minimal needed sensors (up to nine), and controlling the equipment using in-line measured data (closed-loop
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
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operating (Waterstromen) membrane-based wastewater treatment plants. As part of the UT team, you will develop a robust model predictive control (MPC) algorithm based on sensor and other system inputs that can
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engage in immersive, simulated construction tasks, while wearable sensors monitor their physical effort, emotional states, and cognitive load. Physiological and behavioural data — including eye tracking
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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create