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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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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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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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-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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Health, Medical Sensors, Systems Physiology, Internal Medicine Secondments : University of Ulm (D): To work with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling
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: Haukeland University Hospital (HUH) and University of Bergen (UiB), Norway Supervisors: Prof. Marianne Øksnes , Prof. Walter Karlen Duration: 3 years (with possibility of extension) The project includes: Case