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accurate, efficient, and robust AI models capable of operating effectively within complex and dynamic radiofrequency spectral landscapes, accounting for real-world interference, noise, and channel
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algorithmic aspects related to the development of highly accurate, efficient, and robust AI models capable of operating effectively within complex and dynamic radiofrequency spectral landscapes, accounting
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detection of ongoing attacks with well-understood AI methods used for system and network monitoring, (partially) autonomous and explainable reaction to attacks in presence of resource trade-offs and complex
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made Solid background in mathematics, physics and programming Experience in processing or analysis of synthetic aperture radar data You will need strong written and verbal communication skills in English