Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- Curtin University
- SciLifeLab
- Nature Careers
- Technical University of Denmark
- DAAD
- NTNU - Norwegian University of Science and Technology
- Technical University of Munich
- ; University of Leeds
- ; University of Warwick
- Cranfield University
- Humboldt-Stiftung Foundation
- ;
- CWI
- Chalmers University of Technology
- Leibniz
- Monash University
- RMIT University
- Swinburne University of Technology
- University of Twente
- ; Durham University
- ; Manchester Metropolitan University
- ; Swansea University
- ; University of Exeter
- Aalborg University
- Ariel University
- Brookhaven Lab
- Canadian Association for Neuroscience
- Claremont Graduate University
- Cornell University
- Deutsches Elektronen-Synchrotron DESY •
- ETH Zurich
- Fraunhofer-Gesellschaft
- Ghent University
- Hannover Medical School •
- ICN2
- Imperial College London
- Karlsruhe Institute of Technology •
- Linköping University
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Biogeochemistry, Jena
- Max Planck Institute for Human Cognitive and Brain Sciences •
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for Sustainable Materials •
- McGill University
- Mälardalen University
- National Research Council Canada
- Pennsylvania State University
- Queensland University of Technology
- Technische Universität Berlin •
- Umeå University
- University of Copenhagen
- University of Lethbridge
- University of Minnesota
- University of Southern Denmark
- University of Utah
- Universität Hamburg •
- VIB
- Østfold University College
- 48 more »
- « less
-
Field
-
, machine learning techniques may be integrated to accelerate simulations and improve medical image processing, ultimately aiding in stroke diagnosis and treatment planning. Please note that this is a self
-
of MSI advances our understanding of complex brain processes. The prospective PhD candidate collects brain MSI data and develops novel machine learning methods in connection to generative models such as
-
multimodal machine learning. Admission requirements The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits
-
, both written and verbal Knowledge of German and/or a willingness to learn Computer/programming literacy, for example in R, and/or software used in image processing (Adobe Photoshop, ImageJ etc.) Ability
-
, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted
-
research in TRL forward. Theoretical knowledge of, or experience with, machine learning such as representation and generative learning, and natural language processing. Programming skills, e.g. Python, Java
-
structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data analysis techniques, are preferred. Application process To apply
-
publications and research experiences in structural dynamics and structural health monitoring, especially on computer vision, image processing, machine learning, deep learning, signal processing and data
-
to biological data sets such as omics data, protein structure prediction, or biomedical imaging. Technical experience in programming (Python preferred), and/or machine learning is a plus—not a requirement. We
-
to biological data sets such as omics data, protein structure prediction, or biomedical imaging. Technical experience in programming (Python preferred), and/or machine learning is a plus—not a requirement. We