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40 scientists, postdoctoral researchers, and PhD students working on the interpretation of satellite observations, atmospheric modelling, data science, and the development of future Earth observation
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synchronized to each patient's evolving gait dynamics as they recover. You will: Retrain an IMU-based gait-detection algorithm using stroke-patient data Run patient panels with stroke survivors, with a PhD
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system for stroke rehabilitation, test and optimize it with patients, retrain the stimulation-control algorithm for stroke-specific gait, and evaluate usability, comfort, and fit during prolonged use. You
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executed. In close collaboration with PhD researchers and project partners from TUM and ETH, you will contribute to the development of novel control and learning methods for aerial manipulators and multi
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national center for biodiversity information. Among other things, Naturalis runs large-scale ML services for nature recognition, including bioacoustics algorithms developed in the team. What you will do
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sensitivity analyses across pathology severity, body morphology, camera viewpoint, and environmental conditions Develop a single-camera, home-based markerless system Test the algorithm across lab and home
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-camera, home-based markerless system Test the algorithm across lab and home-recorded environments to assess real-world performance Design clinician-facing visualization tools ensuring privacy-by-design
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, including bioacoustics algorithms developed in the team. What you will do Conducting rigorous research at the intersection of ML and wildlife bioacoustics; Actively participating in regular group and one
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, ECCV) and represent the lab at international meetings; help shape the research agenda, co-supervise PhD and MSc students, and contribute to proposals and collaborations (e.g. with industry and clinical
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(Automated Design of Algorithms) group in the machine learning clusters at LIACS, Leiden University, and supervised by Jan van Rijn and Holger Hoos. You will be working intensely with other project members