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3GPP compliant 5G/6G NR NTN OFDM waveforms Develop and analyse signal processing and/or machine learning algorithms for joint channel, delay, Doppler and carrier phase estimation, remote object ranging
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closely related field PhD training covering topics such as computational modelling, numerical methods, statistical analysis, machine learning or data-driven analysis of complex systems Experience 0–3 years
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graphs and related structures, limit theorems, stochastic calculus and applications, for example in machine learning and mathematical statistics Participation in the scientific activities of the department
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machine learning technologies in order to provide evidence-based decision support tools in near real time across a variety of thematic domains: disaster risk reduction, sustainable agri-food systems
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in wireless communications and networking Background in AI and machine learning is an advantage. Experience and skills Knowledge of random-access protocols (e.g. IEEE 802.11 family). Understanding
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well as opportunities for conference attendance and collaborations with other research organisations. Key Skills, Experience and Qualifications PhD in machine learning, computer vision or a related field. Established
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and optimization, we use tools such as artificial intelligence/machine learning, quantum conputing, graph theory, graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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conducts research on the application and the impact of digital technologies like DLT/Blockchain, Digital Identities and Machine Learning/AI on organisations from both the private and public sectors