Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- DAAD
- Leibniz
- Technische Universitaet Dresden
- University of Regensburg
- Catholic University Eichstaett-Ingolstadt
- Deutsches Zentrum für Neurodegenerative Erkrankungen
- Forschungszentrum Jülich
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- Helmholtz-Zentrum Geesthacht
- Helmholtz-Zentrum Hereon
- Leibniz-Institute for Food Systems Biology at the Technical University of Munich
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for the History of Science •
- 4 more »
- « less
-
Field
-
–2 years, total 3–4 years) on deep learning for medical imaging. This DFG-funded project focuses on developing deep learning methods for medical and scientific imaging. The Professorship for Machine
-
03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
-
03.06.2021, Wissenschaftliches Personal The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and
-
well as experience in omics data analysis, and possesses solid English-language skills. Experience with programming, preferably Python and R, is required. Experience with deep learning frameworks, such as JAX
-
Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 27 days ago
the Fugger lab at the Oxford Centre of Neuroinflammation , focusing on the development of drugs that tame common brain diseases through the application of graph-based neural networks, deep learning, and
-
Leibniz-Institute for Food Systems Biology at the Technical University of Munich | Freising, Bayern | Germany | 14 days ago
well as experience in omics data analysis, and possesses solid English-language skills. Experience with programming, preferably Python and R, is required. Experience with deep learning frameworks, such as JAX
-
/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
-
imaging using deep learning. You will study the water imbibition in hierarchically porous Si‑based material systems across multiple length and time scales. These systems can manipulate fluid transport
-
“Stability and Solvability in Deep Learning”. This project focuses on mathematically analyzing machine learning algorithms with a particular focus on questions of stability, computability, and robustness
-
of Science and Freie Universität Berlin, Humboldt-Universität zu Berlin, and Technische Universität Berlin. The IMPRS-KIR traces the deep entanglements of knowledge and its resources from a long-term and