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collaborative project that spans multiple continents. Your main role will be to develop advanced algorithms for multivariate, multi-resolution time series analysis of wearable and neurophysiological data spanning
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LEO, MEO, and GEO constellations), and complementary on-board sensors. Research will investigate algorithms for robust multi-sensor fusion and positioning assurance. A strong emphasis will be placed
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simulation of scenarios with different materials and geometries. - Support the development and implementation of signal and image processing algorithms, including fast inversion techniques, FFT, and nonlinear
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 22 days ago
The spectacular development of space systems and sensors, for observing the Earth and other Planets, provides access to numerous geophysical, geochemical and biophysical parameters over vast areas with increasingly
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PhD Opportunity – Advanced Microwave Sensor Design for Detection Technologies The School of Electrical and Mechanical Engineering at the University of Adelaide is seeking a highly motivated PhD
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in the live organism to study e.g. immune responses or cancer development. Moreover, using molecular sensors we also aim to read out cellular functionality in vivo e.g. metabolic reprogramming in
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Distributed radar systems comprise a coherent network of spatially distributed sensors that can be independently transmitting, receiving, or both. By acting in unison, rather than in isolation
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monitoring. Conventional early-warning systems, such as optical/IR cameras, satellites, human observers, and dense sensor networks, either provide limited warning time, depend on clear visibility, or are too
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a primary emphasis on designing smart algorithms to trigger non-invasive blood pressure (NIBP) measurements at critical times. This will involve leveraging physiological sensor signals such as the
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on integrating sensor-driven data streams and historical datasets into the hybrid digital twin framework, thus enhancing the reliability, safety, and efficiency of SDVs throughout their lifecycle—from design and