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No: 101227148) and coordinated by the University of Bergen, Norway. Supervisors: Prof. Martin Reincke , Prof. Nicole Reisch Location: Ludwig Maximilians University Hospital Munich, Germany Duration: 3 years
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PhD Opportunity – Advanced Microwave Sensor Design for Detection Technologies The School of Electrical and Mechanical Engineering at the University of Adelaide is seeking a highly motivated PhD
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network Research Fields: Hormones, Digital Health, Medical Sensors, Physiology Secondments: University of Ulm (Germany): Algorithms for wearable data analysis University of Manchester (UK): Mathematical
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training courses and workshops of the ENDOTRAIN network Research Fields: Hormones, Digital Health, Medical Sensors, Physiology Secondments: University of Ulm (Germany): Algorithms for wearable data analysis
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depletion, toxic algae, and pollutants. This natural sensitivity makes them powerful bio-sensors for environmental monitoring, capable of providing early warnings of ecosystem stress. However, harnessing this
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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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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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-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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fundamentals of networking. Objectives: To achieve on-device spectrum sensing using on-board sensors of mobile BSs, empowered by embedded deep learning algorithms; to propose an analytical model for the cell