Sort by
Refine Your Search
-
Listed
-
Field
-
Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
-
environment at one of Europe’s largest research establishments Your working place is at Forschungszentrum Julich (group of Prof. H. Hendricks-Franssen); regular exchange with RWTH Aachen (group of Prof. J
-
of Prof. Dr. Axel Klawonn, with temporary periods at Forschungszentrum Jülich in the group of Dr. Andreas Herten. We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender
-
on model behavior. We will divide our work into three thrusts: Thrust A: A first major objective will be to augment classical spike train analysis methods particularly those developed by Prof. Grün and
-
Forschungszentrum Jülich, but the daily place of work will be at University of Cologne in the group of Prof. Dr. Axel Klawonn, with temporary periods at Forschungszentrum Jülich in the group of Dr. Andreas Herten
-
: Design hierarchical models that explicitly capture misspecifications in metabolic models Develop differentiable and scalable inference algorithms using automatic differentiation Implement HPC-tailored
-
physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic environments Design and implement reinforcement learning algorithms for control and