-
to join our dynamic team. As part of the newly funded ERC Synergy consortium EPIC, you will develop scalable and robust software to train and apply AI models for regulatory genomics. About us The Chair of
-
, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
-
efficient algorithms and machine learning/artificial intelligence methods in combination with complex network analysis tools to predict and model interactions between food and biological systems • Further
-
, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
-
, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity distribution grids and thermal energy systems for a sustainable
-
freedom and provide significant potential for increasing the efficiency in today’s train schedules. While this certainly provides a great deal of freedom and potential for improvements, utilizing
-
storage Innovation in the Machine Learning algorithms for EDA in terms of Computational Complexity, Performance Scores, etc. To learn more about our previous work, please check out our website
-
for various technologies and develop algorithms and software tools dedicated to accelerating research on multiple levels. We are working at the intersection of computer science, physics, and material science to
-
to the road? Then this position is just right for you! About us In the Autonomous Vehicle Lab, we develop the vehicle of the future with intelligent algorithms and methods. We are involved in numerous projects
-
efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a sustainable future. These