Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- Nature Careers
- Technical University of Munich
- Leibniz
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- DAAD
- Heidelberg University
- WIAS Berlin
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Sustainable Materials GmbH, Düsseldorf
- University of Tübingen
- Universität Düsseldorf
- 2 more »
- « less
-
Field
-
clocks and laser links between Earth and the international space station ISS. The concrete task is to optimize our strontium lattice clock (DOI: 10.1103/PhysRevA.98.053443), transfer it to the Geodetic
-
on the recently published DeepRVAT framework, which leverages advances in machine learning to learn an optimal rare variant aggregation function in a data-driven manner. You will have the opportunity to spend
-
of fluid dynamic modeling and the analysis of thermomechanical stresses, you will accompany the entire development process – from the optimization of electrochemical performance to the elaboration
-
human patient samples and cutting-edge AI-driven analyses Validate computational findings through functional laboratory experiments Develop and optimize protocols involving omics methods, immune cell
-
spectroscopic or microscopic methods and subsequent optimization Advancements of experiments, measuring methods and measuring technology and improvement of experimental equipment Presentation of results
-
Broadband UV-generation position Push the frontiers of nonlinear optics in multi-pass cells Optimize third harmonic generation in nonlinear gases Develop scaling concepts to kJ pulse energy levels General
-
The research group Agroecological Breeding focuses on optimizing crop mixtures and advancing genetic and omics-based approaches to enhance sustainability in agriculture. Our research aims
-
management of projects in the fields of bioenergy, combustion technology and CO2-neutral process heat with a focus on high-temperature applications Construction, optimization and testing of plants in the pilot
-
genomics, virtual cell models Graph-based neural networks, optimal transport Biomedical imaging, deep learning, virtual reality, AI-driven image analysis Agentic systems, large language models Generative AI
-
improved patient outcomes Integration of findings into translational research, collaborating closely with clinicians, imaging specialists, and bioinformaticians to optimize interventional oncology treatments