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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

, 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

Internet of Things (IoT): LTEM and NBIoT • Satellite communications and be familiar with the principles of • Machine learning/Deep learning • Optimization theory • Linear algebra • Statistical signal

, 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

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

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

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

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

. 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