Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- DAAD
- Forschungszentrum Jülich
- Nature Careers
- RWTH Aachen University
- Fraunhofer-Gesellschaft
- GFZ Helmholtz Centre for Geosciences
- Leibniz
- University of Potsdam •
- Deutsches Elektronen-Synchrotron DESY •
- Forschungsinstitut für Nutztierbiologie (FBN)
- Heraeus Covantics
- Karlsruher Institut für Technologie (KIT)
- Leibniz-Institute for Plant Genetics and Crop Plant Research
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Molecular Genetics •
- Max Planck Institutes
- Ruhr-Universität Bochum •
- Saarland University •
- TU Dresden
- Technische Universitaet Darmstadt
- University of Bremen •
- Universität Düsseldorf
- 13 more »
- « less
-
Field
-
Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
-
Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
-
Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
-
learning (ML) methods—including surrogate modelling, feature extraction, and inverse design algorithms Generate synthetic microstructures (based on the open-source OptiMic software) Perform descriptor
-
Leibniz-Institute for Plant Genetics and Crop Plant Research | Neu Seeland, Brandenburg | Germany | 15 days ago
architecture of important crop traits like grain yield heterosis. In the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck
-
Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience-informed design
-
Virtual Training Environment (VTE) for disaster response simulation, integration of Building Information Modelling (BIM) with Structural Health Monitoring (SHM) using smart sensor networks, and resilience
-
, on fundamental aspects of atomic spectroscopy and quantum physics, and will finally learn how to develop a commercial quantum sensor. Your role: Basic research in the theory and experiments with hot
-
architectures, and demonstration of showcase applications, like light emitters, light sensors, supercapacitors, and batteries. Research and training tasks will be carried out by a collaborative and
-
play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms