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to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
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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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the University of Bergen, Norway. Supervisors: Prof. Martin Reincke , Prof. Nicole Reisch Location: Ludwig Maximilians University Hospital Munich, Germany Duration: 3 years (with possibility of extension) Start
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endocrinology. Research Fields: Endocrinology, Chronobiology, Reproduction, Digital Health, Medical Sensors, Systems Physiology, Internal Medicine Secondments: University of Ulm (D): To work with algorithms
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of integrated and inertial navigation. The working group deals with multisensor systems, i.e. the sensor fusion of GNSS (GPS, Galileo, GLONASS, Beidou), INS (inertial navigation system), cameras, LiDAR (light
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-resolution wearable sensor streams, and endocrine test outcomes. Intelligent Artifact Detection: Develop cutting-edge Machine Learning algorithms to automatically identify, flag, and mitigate data artifacts
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to seamlessly integrate complex hormonal data, high-resolution wearable sensor streams, and endocrine test outcomes. Intelligent Artifact Detection: Develop cutting-edge Machine Learning algorithms
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to source localization based on microphone arrays or distributed sensors. This PhD project will focus on the development of novel methods and algorithms for airborne noise source localization in generic urban
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ABOUT GHENT UNIVERSITY Phd position Markerless Motion Capture using Wearable Sensors Ghent University is a world of its own. Employing more than 15.000 people, it is actively involved in education
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of Oxford. The post is funded by United Kingdom Research and Innovation (UKRI) and is for 24 months. The researcher will develop 3D mapping and reconstruction algorithms with relevance to mobile robotics