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Field
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mobile pigs. By integration sensor data and behaviour obervation, we aim to establish signatures and indicators of sleep and wakefulness in domestic pigs during passive periods. We are now looking for a
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algorithms that can tightly integrate physical hardware, sensors, and computational models. This PhD position is centered on addressing these challenges through innovative computational methods, combining
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geometries and process-induced defects demand new inspection approaches. The project combines modelling, sensor fabrication, experiment, and data analysis. You will work with a team of experts to develop
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. You should be experienced in studying biodiversity, ideally with experience in lone working and the deployment of environmental sensors in a field setting. While you will work in collaboration with
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to sectors such as Geographic Information Systems (GIS), mobility management, the Internet of Things (IoT), and industrial sensorization. Tasks will include: Definition of reusable models and components
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drone detection and localisation performance using radar systems. This can be achieved by improving the detection performance of individual sensors and by employing a cooperative network of sensors which
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and spatially complex nature of MRI signals. Each MRI examination involves multiple pulse sequences, with signal acquisition being sensitive to coil placement, sensor geometry, B0/B1 inhomogeneities
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: Experience with physiological or movement data, such as electrocardiography or wearable sensor data. What else do we offer you We offer a temporary full-time position of 38 hours a week for a term of 4 years
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(GPR), complemented by soil sensors and borehole data. A particular emphasis will be placed on the combined use of borehole and surface GPR, as well as small-scale EMI measurements in controlled
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indicators and neurotransmitter sensors (fiber photometry), opto- and chemogenetics, engram visualization and mouse behavior. By joining our team at the University of Amsterdam, you will contribute to a deeper