Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Forschungszentrum Jülich
- Technical University of Munich
- Leibniz
- DAAD
- Brandenburg University of Technology Cottbus-Senftenberg •
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- CISPA Helmholtz Center for Information Security
- Deutsches Elektronen-Synchrotron DESY •
- Hannover Medical School •
- Helmholtz-Zentrum München
- Heraeus Covantics
- Karlsruhe Institute of Technology •
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Sustainable Materials •
- Nature Careers
- RPTU University of Kaiserslautern-Landau •
- TU Dresden
- Technische Universität Berlin •
- Uni Tuebingen
- University of Tübingen
- 10 more »
- « less
-
Field
-
for machine learning, with research topics ranging from decentralized and federated optimization, adaptive stochastic algorithms, and generalization in deep learning, to robustness, privacy, and security
-
Your Job: In this position, you will be an active part of our "Simulation and Data Lab Applied Machine Learning". Within national and European projects, you will drive the development of cutting
-
30 Sep 2025 Job Information Organisation/Company Uni Tuebingen Department Department of Computer Science Research Field All Researcher Profile First Stage Researcher (R1) Positions PhD Positions
-
mandatory core focus, the PhD position allows room for the individual research interests of the applicant to shape specific aspects—whether in modeling strategy, applied machine learning methods
-
and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
-
Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very latest issues that impact our society
-
processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
-
of topics is covered, from large-scale data management to data mining and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics
-
communication tailored to their needs. For further information, see: https://www.physik.uni-kl.de/oscar/ Course organisation During the research work, the PhD student has the possibility to participate in
-
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremerhaven, Bremen | Germany | about 1 month ago
this PhD, we propose to apply statistical computing combined with machine learning (ML) to the spectrophotometric data to derive high-resolution information on CDOM absorption and its origin. This will be