Sort by
Refine Your Search
-
the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
-
more cost-efficient. Together, UESL and IMOS are seeking a motivated and qualified PhD candidate to advance the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By
-
professional network and build a strong foundation for a future career in academia or industry. Empa actively supports your professional and personal development. The position is initially limited to three years
-
infrastructure, career support, networking opportunities, and competitive salaries. The position is available from April 2026 or after negotiation with a duration of four years. We live a culture of inclusion and
-
and flow field interactions Tuning of the CFD models with experimental results Artificial Neural Network training and development Scientific publications in journals and at conferences Supervision
-
multifractal analysis, urban and energy planning, geography, and artificial intelligence to develop coherent and resilient approaches for urban energy infrastructures under land-use constraints such as No Net
-
) ENDOTRAIN is a Horizon Europe Doctoral Training Network dedicated to transforming the diagnosis and management of adrenal disorders through cutting-edge digital tools. ENDOTRAIN will train a new generation
-
that explicitly incorporates protein–ligand dynamics. You will be responsible for: Designing and implementing innovative deep neural network models. Integrating physical principles and molecular modeling knowledge
-
crucial insights. In this project, you will contribute to the development of AI-driven methodologies for experimental fluid mechanics , focusing on: Designing multi-fidelity neural networks for adaptive
-
networks. The Pertz Lab has developed powerful optogenetic tools and fluorescent biosensors that allow direct perturbation and measurement of these networks using light. Together with the Ginsbourger Group