Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Fraunhofer-Gesellschaft
- Technical University of Munich
- Nature Careers
- University of Tübingen
- Leibniz
- DAAD
- Heidelberg University
- Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ
- Max Planck Institute for Demographic Research (MPIDR)
- Ruhr-Universität Bochum •
- Dresden University of Technology •
- Free University of Berlin
- Helmholtz Centre for Environmental Research - UFZ •
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Demographic Research, Rostock
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig
- Max Planck Institute for Intelligent Systems, Tübingen site, Tübingen
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden
- Saarland University •
- TECHNISCHE UNIVERSITAT DRESDEN (TU DRESDEN)
- Technische Informationsbibliothek (TIB)
- Technische Universität Berlin
- University of Bayreuth •
- University of Bremen •
- 15 more »
- « less
-
Field
-
, a unique opportunity opens up for you: Explore the potential of machine learning and computer vision to revolutionize autonomous flight systems. In close collaboration with leading industry partners
-
, are all essential advancements to enable a wider and more secure deployment of the technology. Most biometric systems are based on image analyses. Therefore, exciting challenges in the computer vision
-
existing technologies, right through to the tested prototype. The Data-based Methods team at Fraunhofer ENAS develops real-world applications using AI, machine learning and computer vision. The main focus is
-
Learning" team has AI expertise and we have a high-performance IT infrastructure available. For our "Computer Vision and Machine Learning" team, we are looking for a student assistant as soon as possible
-
Technische Universität Berlin, Electrical Engineering and Computer Science (Faculty IV) Position ID: Technische Universität Berlin -Electrical Engineering and Computer Science (Faculty IV) -PHD
-
in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages, PyTorch Familiar with foundation models (vision large models or multi
-
computer vision in dusty conditions by incorporating hyperspectral cameras. In addition, assisting in project applications and general development duties of the Chair. The position is available from
-
planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and manipulation strategy adaptation Real-world
-
-tracking technology, Computer Vision, Speech/ Language Processing, VR, and AR. • Know-how/Interest in designing user studies. • Excellent communication skills and a collaborative spirit to work with
-
such as ecology, economy and social sciences. ZMT aims to use data science tools, including computer vision and deep learning, for the study of rapid changes in tropical coastal socioecological systems