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Field
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are rapidly evolving – ranging from remote sensing and automated sensors to genetic techniques and classical field-based inventories. This PhD project focuses on how biodiversity in forests can be measured
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the following research areas providing a template for relevant directions: - Field Robotics with a focus on Arctic Environments - Autonomous Navigation and Motion Planning in Sensor-Degraded Disaster Environments
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centers on developing a framework for controlling a robotic arm equipped with a cardiac ultrasound probe and complementary sensors. The goal is to enable autonomous placement of the probe on predefined
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Distributed radar systems comprise a coherent network of spatially distributed sensors that can be independently transmitting, receiving, or both. By acting in unison, rather than in isolation
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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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the world based solely on research in photonics and electronics. Our photonics research is performed within optical sensors, lasers, LEDs, photovoltaics, ultra-high-speed optical transmission systems, bio
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and automated sensors to genetic techniques and classical field-based inventories. This PhD project focuses on how biodiversity in forests can be measured, monitored, and analysed. The position is
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field studies, and innovative design strategies will be developed that incorporate corrosion-resistant materials, optimised configurations, and embedded Internet of Things (IoT) sensors to monitor
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are categorised as non-destructive testing techniques, but they can be costly considering the number of sensors required and the maintenance of the data acquisition system. Hence, the alternative of direct