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student focusing on the signal processing part in this project, you will be responsible to maximize robustness and signal content of the NIRI brain signals, integrate TMS and NIRI into a combined system
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for physiological signals, embedded systems, signal processing, and physiological modeling related to our previous work . Your profile Prerequisites Candidates should have an excellent master's degree in Electrical
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100%, Zurich, fixed-term The Sensing, Interaction & Perception Lab at ETH Zurich is looking for another PhD student. Our research will be focused on multi-modal signal processing for learning-based
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50%-70%, Ascona, permanent The Congressi Stefano Franscini is ETH Zürichs conference platform on Monte Verità. We provide an ideal meeting point for all members of the international scientific
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: Experience and interest in experimental working Interest in railway Good knowledge of data analysis and signal processing Programming experience Competences in Manufacturing Technology You are highly motivated
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Research Assistant Position: Development of Rail Roughness Measuring Technique and Big Data Analysis
capabilities: Good knowledge of data analysis and signal processing Interest in metrology and measuring techniques Programming experience, preferably in Python and LabView Competences in Information Technology
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-grained activity detection using electromyography sensors as input. Supplemental input modalities will include inertial sensors (IMU). The research will focus on machine learning-based signal processing and
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are seeking a data-savvy and dynamic Membership Officer 50-80%. Job description Your responsibilities include managing our membership database, processing membership applications and renewals, and analysing
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not limited to, signal processing, computer engineering, or computer science towards producing relevant and impactful health-monitoring mobile/wearable solutions, then please apply! The research will be
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: Serve as the key point of contact for project stakeholders, facilitating communication and collaboration to align data management strategies with research goals. Resource Management: Oversee