Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- DAAD
- Forschungszentrum Jülich
- Leibniz
- Nature Careers
- Fraunhofer-Gesellschaft
- International PhD Programme (IPP) Mainz
- Technical University of Munich
- University of Bonn •
- University of Tübingen
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Hannover Medical School •
- Helmholtz-Zentrum Geesthacht
- Ludwig-Maximilians-Universität München •
- RWTH Aachen University
- Technische Universität München
- University of Tübingen •
- 6 more »
- « less
-
Field
-
. D. positions funded by the ERC (European Research Council) to work on the 'EFT-XYZ' (Effective Field Theories to understand and predict the Nature of the XYZ Exotic Hadrons) project-advanced-ERC-2023
-
, you will develop highly accurate computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function
-
computational tools for predicting satellite features in XPS spectra of 2D framework materials. Your work will be based on the GW approximation within Green’s function theory. While the GW method reliably
-
to describe ocean turbulent fluxes #developing theoretical and conceptual models to understand and predict ocean mixing #work as an integrative part of a motivated multidisciplinary team within the institute
-
attractive that the city is predicted to have the highest population growth in NRW. With over 4,800 international students from more than 135 countries, the university contributes significantly
-
highly motivated candidate to develop models integrating machine learning and domain-specific knowledge to predict failure arising from hydrogen embrittlement. You will carry out materials testing
-
. The sub-project of the Phytophotonics department focuses on analysing hyperspectral imaging data for predicting infestations in field crops. The focal topics of the sub-project include: Realisation of a
-
prediction of queue dissolution by combining traffic flow theory with data from roadway and AMOD sensors, nonlinear optimization of the signal plan, cooperative control of traffic signals and AMOD vehicle
-
almost twice the size of New York's Central Park. This urban woodland area is just one of the many places where people can stroll, relax, jog, enjoy nature, or picnic. Hanover's "green ensemble
-
innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools