Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Technical University of Munich
- Forschungszentrum Jülich
- DAAD
- Nature Careers
- Fraunhofer-Gesellschaft
- Leibniz
- Free University of Berlin
- ;
- Deutsches Elektronen-Synchrotron DESY •
- Helmholtz-Zentrum Geesthacht
- Max Planck Institute for Molecular Genetics •
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institutes
- Saarland University •
- University of Tübingen
- 5 more »
- « less
-
Field
-
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
-
. The acronym CAUSE stands for Concepts and Algorithms for - and Usage of - Self-Explaining Digitally Controlled Systems. Digitally controlled systems are ubiquitous in our everyday lives, from transportation
-
The TUM School of Computation, Information and Technology at the Technical University of Munich (TUM) welcomes applications for a PhD or Postdoc Position (m/f/d, 100%, 2 years+) in Numerical Mathematics
-
, algorithm design, optimisation and simulation, software engineering and automation and control systems. An overview of the current PhD research projects is given here: https://www.dashh.org/research
-
algorithms to analyze OMICS data (e.g., genome, transcriptome, proteome, microbiome) from patient samples and basic research perform single-cell RNA-Seq and spatial transcriptomics analysis apply artificial
-
-sampling data. Furthermore, the position holder will play a central role in creating high-quality training datasets (seagrass maps) to support artificial intelligence (AI) algorithms used in related projects
-
quantum processors using this technological platform design and implement optimization techniques for full-stack improvement of quantum algorithms model major sources of experimental error for control
-
algorithms model major sources of experimental error for control theory or co-design methods Previous works can be found under the bibliographies of Dr. Felix Motzoi and and Dr. Matthias Müller: https