Sort by
Refine Your Search
-
Listed
-
Employer
- Fraunhofer-Gesellschaft
- Nature Careers
- Technical University of Munich
- Leibniz
- DAAD
- Free University of Berlin
- University of Tübingen
- Forschungszentrum Jülich
- Heidelberg University
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute of Geoanthropology, Jena
- University of Technology Nuremberg;
- ;
- Constructor University Bremen gGmbH
- Heinrich-Heine-Universität Düsseldorf
- Hult
- Max Planck Institute for Biological Cybernetics, Tübingen
- Max Planck Institute for Innovation and Competition, Munich
- Max Planck Institute for the History of Science, Berlin
- Max Planck Institute of Biochemistry, Martinsried
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden
- Technische Universität München
- University Medical Center of the Johannes Gutenberg University Mainz
- 13 more »
- « less
-
Field
-
that can be used to compare the arrangements • You select suitable algorithms to evaluate the quality of the PPG signals (machine learning, Python) What we offer We offer you a challenging and varied
-
Your Job: Machine Learning (ML) and artificial intelligence (AI) based on neural networks are currently reshaping all aspects of society. In several areas, such as medicine, AI-based tools
-
industrial objects. Different acquisition devices are used depending on the object properties and quality requirements. We research modern machine-learning methods for the analysis of an object's optical
-
want to hear from you! Your Job: Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant
-
our group "Computer Vision and Machine Learning" in developing AI models and transferring them into production. In the master's thesis "Exploring latent spaces of deep networks for fault analysis in
-
, machine learning, energy technology or related subjects Prior experience in building predictive models using regression techniques, neural networks (CNN, GNN) or symbolic regression Experience in
-
) Intense interaction with consortium Your Profile: Master and PhD degree in materials science, physics, chemistry, informatics, machine learning, energy technology or related subjects Prior experience in
-
11.12.2025 Application deadline: 15.02.2026 The Faculty of Science at Tübingen University invites applications for a W3-Professorship in Machine Learning in Physics at the Department of Physics (m/f
-
of Mathematics and Natural Sciences at Heinrich Heine University Düsseldorf is inviting applications for the position of a Professorship for Machine Learning (open rank: W2 or W1 with tenure track to W2
-
and manufacturing technologies for the manufacture of innovative products. We develop new machines and processing strategies on behalf of customers, optimize existing production systems and implement