Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- DAAD
- Technical University of Munich
- Humboldt-Stiftung Foundation
- Nature Careers
- Forschungszentrum Jülich
- Leibniz
- Deutsches Elektronen-Synchrotron DESY •
- Fraunhofer-Gesellschaft
- Hannover Medical School •
- Karlsruhe Institute of Technology •
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for Sustainable Materials GmbH, Düsseldorf
- Max Planck Institute for Sustainable Materials •
- TU Dresden
- Technische Universität Berlin •
- Universität Hamburg •
- 8 more »
- « less
-
Field
-
cutting-edge methods in chemical, mechanical, and plasma processing of metal ores for a truly circular economy. Correlating experimental, ab initio and multi-scale simulation as well as machine learning
-
learning, or signal processing; familiarity with microscopy data is an asset but not required Interest in foundational machine learning research with applied impact in scientific imaging Demonstrated
-
that exhibit emergent turbulent behaviors, and (2) disordered optical media that process information through complex light scattering patterns. Using advanced imaging, machine learning techniques, and real-time
-
the opportunity to contribute to collaborative efforts at the interface of data science, imaging, and materials research. You will strengthen the data science and machine learning activities of the IAS-9 with
-
/biomedical engineering or of relevant scientific field A solid background in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages
-
and curate LC-MS/MS data for high-quality feature extraction Design and train machine-learning models for mass spectrometry and chemometric data Integrate multi-omic data including genomics and
-
domains are e.g., signal-/image processing, artificial intelligence and machine learning. Tasks: research and development in designing and programming field programmable gate arrays (FPGAs) for accelerating
-
Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
-
the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
-
learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms