Sort by
Refine Your Search
-
Category
-
Employer
- Technical University of Munich
- Catholic University Eichstaett-Ingolstadt
- Fraunhofer-Gesellschaft
- German Cancer Research Center in the Helmholtz Association (DKFZ)
- Heidelberg Institute for Theoretical Studies (HITS gGmbH)
- Heidelberg University
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- Max Planck Institute for the History of Science •
- Saarland University
- Technische Universitaet Dresden
- Technische Universität Dresden (TU Dresden)
- Technische Universität München
- 2 more »
- « less
-
Field
-
Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | about 12 hours ago
) in Geometric Deep Learning to join the Machine Learning and Artificial Intelligence (MLI) g roup to perform research in geometric deep learning for materials science. This research is part of
-
–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
-
are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. We are working
-
foundations of medical deep learning. The project focuses on novel self-supervised objectives, information geometry, mitigating representation bias for rare pathological findings, and building next-generation
-
Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Oct 2026 - 00:00 (Europe/Brussels) Country Germany Type of Contract Temporary Job Status Part-time Is the job
-
Machine Learning at the KU Eichstätt-Ingolstadt is seeking highly motivated candidates for a part-time position (75%) at the next possible date as a PhD Student (m/f/d) with contract duration of 3 years
-
PhD candidate who shares our deep interest in exploring conceptual, educational, social, and governance issues that emerge in the context of scientific modelling. The candidate also brings the following
-
FieldComputer scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Strong foundations in Machine Learning and Deep Learning Excellent Python programming skills Experience with PyTorch
-
-style models. Pretraining may use self-supervised, contrastive, masked-modelling, or generative objectives. Own research ideas are strongly encouraged. Your responsibilities • Develop deep learning
-
engineering Engineering » Electrical engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 18 Sep 2026 - 23:59 (Europe/Brussels) Country Germany Type