Sort by
Refine Your Search
-
experimental studies, mechanistic modelling, time-resolved data analysis, and machine learning to develop and validate predictive models linking process signals to reaction behaviour, progressing from controlled
-
chain, ranging from synthesis, cell assembly, characterization, modeling to scaled-up manufacturing. The 2-year postdoctoral project Machine Learning-based Electro-Chemo-Mechanical Estimation and Control
-
, the mechanical state of the wall, or a defined combination of both. The resolved model will also predict the conditions under which the wall fails, with direct relevance to controlled, low-energy cell disruption
-
for the diagnosis and prediction of lithium-ion battery ageing. About us At the department of Electrical Engineering research and education are performed in the areas of Systems and Control, Communications, Signal
-
robotics – reinforcement learning, whole-body model predictive control (MPC), and differentiable optimal control – to simulate human balance and step recovery in urban transport scenarios. The goal is a
-
researchers focussing on modelling, estimation and prediction related to battery systems, ranging from details on micro-scale in cells to cloud calculations for fleets of electric vehicles. About the research
-
production, recycling and value chain optimisation. The research focuses on applied AI in areas such as sensor data analysis, time series modelling, automation and decision support, with strong links