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-centered devices considering, for example, the EOBD protocol, is an advantage Background in statistical computing and data analysis. Experience with R or Python is an advantage Solid development skills
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Technology, Experimental and Conceptual Modelling in Ecohydrology, optimality principles) and Christophe Ley (University of Ghent, Bayesian Statistics, Applied Probability). You will be working as part of
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Internet of Things (IoT): LTE-M and NB-IoT • Satellite communications and be familiar with the principles of • Machine learning/Deep learning • Optimization theory • Linear algebra • Statistical signal
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, optimality principles) and Christophe Ley (University of Ghent, Bayesian Statistics, Applied Probability). Framework: You will be working as part of DRIVEN Doctoral Training Unit (DTU) funded by the FNR PRIDE
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, prototype development or technical reports. This can potentially be done through a PhD research work. Profile Education Master in Computer Sciences Competencies Background in statistical computing, data
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Satellite communications and be familiar with the principles of Machine learning/Deep learning Optimization theory Linear algebra Statistical signal processing Programming skills: MATLAB, Python or C
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of machine/deep learning in wireless communications and IoT networks and be familiar with the principles of Optimization theory Machine/deep learning Statistical signal processing Programming skills: familiar
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researcher will be under the supervision of Prof. Gautam Tripathi. Profile PhD degree in Economics/Statistics with a focus on econometrics. Very good English language skills. Willingness to work in an inter
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DRIVEN related discipline, i.e. Computer science, mathematics, statistics or computational engineering with a strong interest in social sciences Strong background in quantitative methods and statistical
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. Optional: knowledge of machine learning, metaheuristics, statistics, and text analysis. Language Skills: Fluent written and verbal communication skills in English are required. We Offer: The University