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cookie and refresh page to watch video, or click here to open video) About the position Distributed machine learning takes advantage of communication and distributed computing to utilise distributed data
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allowing to recognize, summarize, translate, predict, and generate contents using medium to large or very large datasets: in particular new approaches based on Large Language Models (LLM) will require
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communications; (2) low-latency and time-constrained communication; (3) satellite and non-terrestrial networking; (4) interplay between AI/ML learning/inference and communications; (5) communication and sensing
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present some limitations in the range of behaviour they can supply and situations where they can be used. Global Navigation Satellite Systems (GNSS) combined to real-time kinematics (RTK) technology give
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emphasizes principled modeling, reproducible experimentation with open datasets and simulations, and publication-ready contributions targeting leading venues in machine learning and wireless communications
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terrestrial laser scanning data (ALS, TLS), satellite and aerial images. Collecting field data as well as participating in burning experiments may also be part of the work. The research team includes expertise
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emphasizes principled modeling, reproducible experimentation with open datasets and simulations, and publication-ready contributions targeting leading venues in machine learning and wireless communications
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description This project addresses the effective design of a military supply logistics network, composed of transportation and communication links such as roads and rail, aerial drone routes, and nodes, such as
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/ionospheric corrections), with an emphasis on operational, large-scale satellite SAR datasets such as Sentinel-1 and NISAR. Apply technical skills to improve the state-of-the-art within relevant application
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ranging from optical fiber communications, metrology, environmental and medical sensing and imaging, and for applications in fundamental sciences such as laser spectroscopy. The hybrid integration of III-V