Sort by
Refine Your Search
-
Listed
-
Employer
- Nature Careers
- Technical University of Munich
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- University of Tübingen
- Academic Europe
- DAAD
- Heidelberg University
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- Leibniz
- TECHNISCHE UNIVERSITAT DRESDEN (TU DRESDEN)
- ;
- BioMed X GmbH
- Deutsches Elektronen-Synchrotron DESY
- Free University of Berlin
- Hochschule München University of Applied Sciences
- Leibniz Centre for Agricultural Landscape Research (ZALF)
- Max Delbrück Center
- Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen
- Max Planck Institute of Geoanthropology, Jena
- Otto-von-Guericke-Universität Magdeburg
- Technische Informationsbibliothek (TIB)
- University of Bremen
- 13 more »
- « less
-
Field
-
Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 2 hours ago
Job Code: Tue_92 Job Offer from April 22, 2025 The Max Planck Institute for Intelligent Systems is a world leading research institute in artificial intelligence, machine learning, and robotics
-
Dust Analyser onboard the Cassini space probe - Collaboration with a computer scientist who is developing a machine learning (ML) algorithm for the automated analysis of the above-mentioned mass spectra
-
optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! What
-
related field Sound knowledge in the field of artificial intelligence and machine learning Ideally experience with knowledge graphs, semantic search, graph neural networks (GNNs), explainability
-
, Computational Science, or a related field; a PhD or equivalent experience is preferred Strong programming skills in Python, with experience in machine learning frameworks such as PyTorch or TensorFlow
-
the contribution of genetic and non-genetic driving forces for the cells’ evolution and glioma development. Using multi-omics data integration and machine learning, we will investigate cellular
-
researcher with a proven track record in areas relevant to auto-tuning, focusing on ML-driven compiler optimization, transfer learning, and programming for heterogeneous systems across CPUs, GPUs, and
-
researcher with a proven track record in areas relevant to auto-tuning, focusing on ML-driven compiler optimization, transfer learning, and programming for heterogeneous systems across CPUs, GPUs, and
-
equivalent in bioinformatics, computational biology or molecular biology • Practical experience with programming, machine learning, statistical analyses of big data and bioinformatics tools and software
-
opportunities to learn, develop, and apply machine learning and deep learning methods on genomics data. Requirements: excellent university and PhD degree with experience in molecular biology, computational