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Field
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) sensor data. This will be a small system-on-chip designed to operate on the edge (i.e. close to the sensor). The project will explore whether emerging logic-based ML algorithms can be translated
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an adaptable Machine Learning (ML) hardware architecture to solve Artificial Intelligence (AI) classification tasks using Internet of Things (IoT) sensor data. This will be a small system-on-chip designed
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project’s focus is to: Conduct cutting-edge experiments to investigate how surface texture affects seal performance and explore the use of an ultrasonic sensor for real-time monitoring. Experiment with
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integrated in a removable smart denture. The project targets the integration an advanced micro-system comprising sensors, micro-fluidics, and a sophisticated drug delivery system. The complex 3D printed
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drugs at the target site, using only an internal battery and on-board sensors for fully autonomous operation. The overarching goal is to develop a battery-powered ingestible capsule that autonomously
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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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characterization to device integration. You will fabricate and test cutting-edge device architectures, including 2D Complementary FETs (CFETs), memory devices, and sensors, pushing the boundaries of what's possible
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-594 Is the Job related to staff position within a Research Infrastructure? No Offer Description Development of electrochemical sensors for the detection of PFAS in environmental and food samples PFAS
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communication and sensor systems. Design, model, and experimentally characterize sustainable antennas and wireless system components for Internet of Things (IoT) and industrial applications. Explore approaches
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microclimates that demand dense sensor networks and reliable data retrieval. This project focuses on developing nature-inspired hardware to deploy Internet of Things (IoT) sensors in forest ecosystems. Combining