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Field
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Challenge: Building self-organizing edge infrastructure that seamlessly adapts across terrestrial, cloud, and satellite networks. Change: Creating autonomous systems that unify edge orchestration
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mechanical stress into useful electrical energy, enabling autonomous sensors and systems in demanding industrial and structural environments. The research will involve a combination of analytical modelling
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Experience in designing software systems General overview and understanding of the working principles of sensors and robotics Applicants are invited to submit a research plan outlining their approach
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- Rad) provide continuous but coarse radiative fields (5–30 km). High-resolution sensors such as Sentinel-2, Landsat, ECOSTRESS, and SDGSAT-1 offer fine spatial detail but sparse temporal coverage and
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one of the following areas: scientific programming and data analysis (e.g., Python, R, C++, MATLAB), computational modeling, imaging and sensor data processing, bioinformatics, systems biology, or
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involved in: Analysis of data from medium and low-cost sensors Analysis of data from cognitive performance assessments and health survey responses Conduction citizen science-based activities in the schools
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and adapted tools for the processing of signals or images acquired with biomedical sensor networks (cardiology, neurosciences) or in geosciences (seismology and marine ecology), but also in wireless
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expertise on animal breeding, biological understanding of traits of cattle, swine, poultry and fish and sensor technology and big data analyses. We perform research in quantitative genetics, genomics, animal
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completely sustainable and future-proof. At 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
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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 AI. Meanwhile we