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the sensors measured? In the ASPIRE project, we develop knowledge for the new generation of sports tracking technology that integrates athletes’ subjective experiences (such as perceived exertion, motivation
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universities, with access to unique deposition and test facilities and strong international collaboration networks. This position provides the opportunity to contribute directly to the energy transition and to
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Trustworthy Graph Machine Learning for Population Scale Networks Job description We invite applications for a postdoctoral researcher to work on fundamental techniques for trustworthy graph machine
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the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting
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an inspiring research setting at one of Europe’s leading technical universities, with access to unique deposition and test facilities and strong international collaboration networks. This position provides
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discipline. A strong curiosity for human gait and neuromuscular control after stroke. Experience with wearable-sensor (IMU) data and human motion analysis. Solid programming skills (ideally, in Python
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wearable-sensor (IMU) data and human motion analysis. Solid programming skills (ideally, in Python) for algorithm development, control design, and data analysis. Confidence and interest in testing and
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the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes
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of Earth Observation Programmes at ESA’s Earth observation centre: ESRIN. The Division is responsible for the management of ESA’s Earth observation missions, the development of the ground processors, sensor
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for everyone, meaning there is space for each individual's culture, background, ideas, and creativity. In our excellent network with top-tier AI-research groups (e.g. from ETH Zurich, Stanford, Heidelberg