Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- Nature Careers
- Leibniz
- Forschungszentrum Jülich
- Heidelberg University
- Karlsruher Institut für Technologie (KIT)
- Leibniz Institute for Plasma Science and Technology
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Deutsches Zentrum für Neurodegenerative Erkrankungen
- FUB - Free University of Berlin
- Free University of Berlin
- Fritz Haber Institute of the Max Planck Society, Berlin
- GFZ Helmholtz-Zentrum für Geoforschung
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Institute for X-Ray Physics, University of Göttingen
- Leibniz Institute for Neurobiology
- Max Planck Institute for Astronomy, Arua, Uganda
- Max Planck Institute for Astronomy, Heidelberg
- Max Planck Institute for Brain Research, Frankfurt am Main
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for Radio Astronomy, Bonn
- Max Planck Institute for Solid State Research, Stuttgart
- Ruhr-Universität Bochum
- Universitaetsklinikum Erlangen
- University of Bremen
- University of Hamburg
- WIAS Berlin
- 18 more »
- « less
-
Field
-
static and dynamic 3D reconstruction, semantic scene understanding, and generative models for photo-realistic image / video synthesis. Overall, the main focus is on high-impact research with the aim
-
18.10.2022, Wissenschaftliches Personal The lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is looking for a Post-Doc. The task will be the multi-modal modeling of medical data
-
energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes
-
. Detection and imaging of electrical signals in neurons, the cells performing computation in our brain. You will work towards this goal by one of two complementary approaches: testing new quantum materials
-
Enthusiasm for an exciting new computing paradigm involving the development of innovative solutions Openness to communicate, cooperate and exchange ideas within a joint endeavor of multiple vibrant research
-
with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
-
with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
-
interactions with such environments. We investigate machine learning approaches to infer semantic understanding of real-world scenes and the objects inside them from visual data, including images and depth/3D
-
in static and dynamic 3D reconstruction, semantic scene understanding, and generative models for photo-realistic image/video synthesis. Overall, the main focus is on high-impact research with the aim
-
validate designs of microfluidic devices even before the first prototype is fabricated. In this field, we are about to start a consortial project with stakeholders from academia and industry to establish