-
into four research thrusts that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics The objective
-
engineering, acoustics, machine learning or similar; Solid mathematical and analytical skills, including signal processing, optimization, machine learning or information theory; Experience in programming, e.g
-
degree or equivalent in Energy Engineering, Electrical Engineering, Mathematics, Control theory, or any other related discipline, potentially with skills in Power Electronics Converters and Control
-
academic background with a master’s degree or equivalent in Energy Engineering, Electrical Engineering, Mathematics, Control theory, or any other related discipline, potentially with skills in Power
-
volatility. CLASSIQUE is organized into four research thrusts that rely upon interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and
-
computing technologies. The group has a long tradition of empirical and solution-oriented research focusing on processes, products, and theory. The PhD fellow will join the Human Augmentation and
-
, conducting theory-driven statistical analyses of longitudinal register data, and, where relevant, linking these with existing survey data. The PhD student will contribute to international journal publications