Sort by
Refine Your Search
-
computational methods using network-based analysis, machine learning and dynamic modeling. We are a young, dynamic team at the idyllic Dahlem campus and teach mainly in the Computer Science, Bioinformatics and
-
is the role of clouds in the climate system. For this, we apply and develop a wide range of numerical approaches that cover highly idealized heuristic models to very detailed Lagrangian representations
-
knowledge from Ordinary Differential Equations (ODEs) with active learning strategies. The goal is to make ML models more flexible, efficient, and reliable, especially when working with limited data. Detailed
-
computational models with the "exact" but lower resolution information available from experiments. Job description: Application of specially developed approaches to define for transferable force-fields with
-
CRC 1114 aims at methodological developments for the modelling and computational simulation of complex processes involving many (more than two) interacting scales, driven by real-life applications
-
), and computational modeling (deep neural networks). We apply multivariate analysis methods (machine learning, representational similarity analysis) and encoding models. Job description: This is an open
-
computational models with the "exact" but lower resolution information available from experiments. Job description: - Research and teaching is done on statistical physics and machine learning in physics
-
mechanisms. Job description: • Research and development in the field of AI-supported analysis of biomedical data • Implementation and evaluation of methods for AI validation and model interpretability
-
to understand why the liberal model of order has fallen into crisis despite its political, economic, and social achievements. SCRIPTS has been operating since 2019 and is funded by the German Research