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-identified scans, records and sensor feeds to answer questions such as: Can we predict a patient’s response to treatment without ever seeing their raw file? Can an algorithm learn the warning signs of trouble
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, thermal, electromagnetic or kinetic), are critical for the sustainable operation of wireless IoT devices and remote sensors. The world can reduce reliance on batteries and fossil-fuel-derived power if more
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, advanced materials, and sensor development, while also addressing key robotic challenges such as real-time process monitoring and diagnostics in inaccessible or hazardous environments. We have discussed a
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. It will use signals from different sources—such as radio signals and internal sensors— to maintain robust and accurate PNT, even when satellite signals are weak or missing. A built-in intelligent
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Details A brain-computer interface (BCI) provides a direct communication pathway between a human brain and an external device. Using appropriate sensors and data processing algorithms, a BCI maps patterns
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and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected from in-service
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the ground, in different weather conditions. 4) develop methods for sensor management and data fusion linked with inference and decision making, jointly applied to several wildfire detection tasks. 5) embed
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, path finding and routing algorithms, sense of direction, human computer interaction, cognitive navigation, intelligent mobility, and artificial intelligence. Sensor fusion and Signals of Opportunity We
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Lyudmila Mihaylova Application Deadline: Applications accepted all year round Details This PhD research is focused on multi-sensor data fusion for decision making. The project aims at dealing with large
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directly and relate them to structural and functional outcomes. In parallel, you will develop new sensors for intracellular potassium concentration leveraging AI based protein design algorithms. Techniques