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Field
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drones and process data of multispectral, thermal and LiDAR sensors Implement approaches to integrate drone data into an existing agroecosystem data assimilation framework Use radiative transfer models
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our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors
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–robot interaction and ergonomics Automation and robotised workplaces (industry use-cases) Field robotics and harsh-environment robotics Predictive maintenance, sensor systems, multimodal monitoring AI/ML
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–robot interaction and ergonomics Automation and robotised workplaces (industry use-cases) Field robotics and harsh-environment robotics Predictive maintenance, sensor systems, multimodal monitoring AI/ML
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This is a four-year (1+3 MRes/PhD) studentship funded through the Cambridge EPSRC Centre for Doctoral Training in Future Infrastructure and Built Environment: Unlocking Net Zero (FIBE3 CDT). Further
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annotation platforms. The candidate will collect plankton images using an innovative benchtop flow-through imaging sensor, integrating them with existing datasets from established platforms. They will also
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using accessible programming languages and annotation platforms. The candidate will collect plankton images using an innovative benchtop flow-through imaging sensor, integrating them with existing
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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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micro energy and smart sensing devices to tackle long-term challenges like “Healthier Citizens” and “Net Zero Human Impact.” She has collaborated for over 20 years with Aitor on projects related
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• Experience in bio-instrumentation design, specifically in integrating biological or chemical assays with electronic sensors • Experience with NFC technology • Experience developing mobile applications