Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Forschungszentrum Jülich
- Technical University of Munich
- DAAD
- Fraunhofer-Gesellschaft
- Leibniz
- Nature Careers
- Heidelberg University
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- GFZ Helmholtz Centre for Geosciences
- CISPA Helmholtz Center for Information Security
- Constructor University Bremen gGmbH
- Deutsches Elektronen-Synchrotron DESY
- GFZ Helmholtz-Zentrum für Geoforschung
- Hannover Medical School •
- Helmholtz Zentrum Hereon
- Helmholtz-Zentrum Geesthacht
- Helmholtz-Zentrum München
- Heraeus Covantics
- Karlsruher Institut für Technologie (KIT)
- Leipzig University •
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Gravitational Physics, Potsdam-Golm
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig
- Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen
- Max Planck Institute for Meteorology •
- Max Planck Institute for Sustainable Materials GmbH, Düsseldorf
- Max Planck Institute for Sustainable Materials •
- Max Planck Institute of Biochemistry, Martinsried
- RWTH Aachen University
- Technische Universität Berlin •
- University of Münster •
- 22 more »
- « less
-
Field
-
performance in fuel cell (biogas) and co-electrolysis applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under
-
applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under various operating conditions and develop strategies
-
at demonstrating how teacher learning can be made robust in an event-based framework, that is, when both the teacher model and the learning rules are event- based. The combination of excitable teacher dynamics and
-
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
-
direction (possibly forming spontaneous “lanes”), crossing, and opposite flows. For single-lane vehicular traffic, the model should revert to a car-following model. In cooperation with the supervisor Dr
-
and machine learning to establish a modeling framework that uses omic data for providing effective degradation rates of biomolecules and predictions of their impact on soil organic matter turnover
-
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Bremen, Bremen | Germany | about 2 months ago
enabler of machine learning for eDNA-based assessments of deep-sea ecosystems” (m/f/d) Background Deep-sea ecosystems host highly diverse biological communities that provide key ecosystem functions and
-
strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists, software developers and domain
-
-harvesting complexes. The research will use a combination of quantum and molecular dynamics simulations, electronic structure calculations, and machine learning approaches. These are similar to earlier work
-
The Network Analysis and Modelling uses machine learning to investigate how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. We are seeking a