Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Technical University of Munich
- Fraunhofer-Gesellschaft
- Nature Careers
- Leibniz
- DAAD
- Forschungszentrum Jülich
- Humboldt-Stiftung Foundation
- Heidelberg University
- Deutsches Elektronen-Synchrotron DESY •
- Deutsches Zentrum für Neurodegenerative Erkrankungen
- German Cancer Research Center
- Hannover Medical School •
- Karlsruhe Institute of Technology •
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for Brain Research, Frankfurt am Main
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for Sustainable Materials •
- TU Dresden
- Technische Universität Berlin •
- Universität Hamburg •
- 13 more »
- « less
-
Field
-
/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
-
data Strong analytical, problem-solving and communication skills Ability to work successfully both independently in a multidisciplinary team of biologists, physicists, and computer scientists Excellent
-
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
-
are in engineering sciences, mathematics, computer sciences, natural sciences and medicine. Our economics, social sciences and humanities are indispensable and crucial disciplines in a modern university
-
optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
-
optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
-
architecture exploration, hardware/software co-design and operating/runtime systems. Typical application domains are e.g. signal-/image processing, artificial intelligence and machine learning. Tasks: research
-
between the fields of computer sciences and architecture. The focus lies mainly on Building Information Modelling, decision-support methods in urban planning and knowledge-based design methods. As part of
-
collisions and maximize efficiency through innovative AI-based movement and maneuver planning. For the first time, innovative machine learning concepts, such as “shadow learning”, are being used. Appropriate