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Medicine Secondments: University of Ulm (D): To work with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling of hormone rhythms. University of Bristol (UK): To learn
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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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: University of Ulm (D): To work with algorithms for wearable data University of Manchester (UK): To learn mathematical modelling of hormone rhythms. For further details, please visit our webpages Optimized
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, boosted by AI-data augmentation for extrapolating spectrum patterns from multiple sources. To design a scalable computing framework using a physics-informed neural network for distributed spectrum analysis
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systems strong analytical and problem-solving skills fluency in English, both written and spoken Not required, but helpful: Experience with biomedical data/algorithms An affinity for applications
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Not required, but helpful: Experience with biomedical data/algorithms An affinity for applications of technology Contributions to open source projects This is what we offer A temporary contract for 38
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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geometry altogether and operate in hyperbolic space. Our lab has published multiple papers showing that hyperbolic deep learning has strong potential for computer vision, from hyperbolic image segmentation
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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 area of enzyme engineering to the next level, while having a positive impact on our world. When joining our group, you get the opportunity to use the latest algorithms in machine learning for improving