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off-the-shelf sensors and the development of resilient algorithms that combine first-principles modeling with modern machine learning techniques. The goal is to push the boundaries of robust perception
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agricultural robotics and new sustainable farming practices. The PhD projects will be combining new sensor systems and perception algorithms. So, if you are one of the 2 selected applicants, your primary
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optimization algorithms, you will design structures that deliberately harness modal couplings to exhibit tailored nonlinear behaviour, with direct applications in ultrasensitive resonant sensing. Together
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the second direction, you will explore the geometric design of nonlinear systems. Using nonlinear reduced order modelling (ROM) integrated with optimization algorithms, you will design structures
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available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. MPCs excel in handling constrained optimizations and new operational conditions, whereas RLs
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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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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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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power consumption and
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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms