Sort by
Refine Your Search
-
Listed
-
Employer
- DAAD
- Technical University of Munich
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- Nature Careers
- Humboldt-Stiftung Foundation
- Justus Liebig University Giessen •
- Leibniz
- Ludwig-Maximilians-Universität München •
- Ruhr-Universität Bochum •
- University of Potsdam •
- Carl von Ossietzky University of Oldenburg •
- Deutsches Elektronen-Synchrotron DESY •
- German Cancer Research Center (DKFZ) Heidelberg •
- Helmholtz-Zentrum Geesthacht
- Humboldt-Universität zu Berlin •
- Leibniz Institute of Ecological Urban and Regional Development (IOER) •
- Leipzig University •
- Max Planck Institute for Molecular Genetics •
- Max Planck Institute for the Physics of Complex Systems •
- Max Planck Institute of Immunobiology and Epigenetics •
- Max Planck Institutes
- Saarland University •
- Technical University of Darmstadt •
- The Max Planck Institute for Neurobiology of Behavior – caesar •
- University of Bayreuth •
- University of Bremen •
- University of Kassel •
- University of Mannheim •
- Universität Hamburg •
- 20 more »
- « less
-
Field
-
of superconducting qubits to quantify performance and identify limiting physical mechanisms Perform quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research
-
: 01.10.2025 Application deadline: 03.09.2025 Tasks Execution of experimental work in a mouse model of cortical multiple sclerosis Application of in vivo imaging and quantitative analysis methods Investigation
-
the timing of irrigation develop detection algorithms to identify signals in cloud and precipitation properties during periods of irrigation activities analyse interactions between irrigation, clouds, and
-
analysis, with possible specialisations in genomic and molecular biology techniques as well as in algorithms, statistics and artificial intelligence for molecular genetics. This is based on perspective and
-
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. Furthermore, we
-
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. Furthermore, we
-
welcomes international students from 117 countries. The U Bremen Research Alliance offers support with the transition to Germany through its Welcome Center. Training the next generation of researchers
-
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. Furthermore, we
-
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. Furthermore, we
-
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. Furthermore, we