Sort by
Refine Your Search
-
Listed
-
Employer
- Fraunhofer-Gesellschaft
- Technical University of Munich
- DAAD
- Forschungszentrum Jülich
- Nature Careers
- Leibniz
- Saarland University
- Deutsches Zentrum für Neurodegenerative Erkrankungen
- Helmholtz-Zentrum Berlin für Materialien und Energie
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- NEC Laboratories Europe GmbH
- University of Potsdam, Faculty of Science
- University of Tübingen
- Universitätsklinikum Heidelberg – UK Mannheim GmbH
- 4 more »
- « less
-
Field
-
energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical energy management systems (EMS) controlling complex energy systems like buildings, electricity
-
with OSL: Use OSL to implement the PPTBF algorithm in 3D environments: like a couple of point process, feature function and window function. Optimize Procedural Algorithms: Develop more efficient methods
-
manipulation detection. Another focus is the development of algorithms for the areas of virtual product development, intelligent actuator-sensor systems and audio for the automotive sector. There are currently
-
of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning
-
evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine
-
The particular strength of the Fraunhofer Institute for Electronic Nano Systems ENAS lies in the development of smart systems for various applications. The systems combine electronic components
-
processing workflows including QC and reproducibility metrics * APIs and packages supporting the development of new algorithms spanning large * language modeling of DNA and RNA sequences, and algorithms
-
The particular strength of the Fraunhofer Institute for Electronic Nano Systems ENAS lies in the development of smart systems - so-called intelligent systems for various applications. The systems
-
, Metric Learning, Reinforcement Learning, Graph Representation Learning, Generative Models, Domain Adaptation, etc.) for Design Automation applications. To this end, we focus on developing general methods
-
technologies and develop algorithms and software tools dedicated to accelerating research on multiple levels. We are working at the intersection of computer science, physics, and material science to push the