Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- SciLifeLab
- Umeå University
- Lunds universitet
- Linköping University
- Uppsala universitet
- Blekinge Institute of Technology
- The Faculty of Technology and Society
- University of Lund
- Lulea University of Technology
- Luleå University of Technology
- Swedish University of Agricultural Sciences
- Umeå universitet
- Umeå universitet stipendiemodul
- University of Skövde
- Örebro University
- European Magnetism Association EMA
- Göteborgs universitet
- Helmholtz-Zentrum München
- Karlstads universitet
- Karolinska Institutet, doctoral positions
- Linnaeus University
- The Swedish University of Agricultural Sciences
- The University of Gothenburg
- The University of Skövde
- Uppsala University
- universitypositions
- 18 more »
- « less
-
Field
-
most is how close you stay to nature here. Read more and apply: https://www.umu.se/en/work-with-us/open-positions/assistant-professor-in-computing-science-with-a-focus-on-machine-learning---linked
-
are looking for a Research Assistant in Machine Learning and Multimodal Digital Biomarkers with a focus on voice biomarkers, wearable sensing technologies, and performance monitoring, at the Department
-
. Learn more about the initiative and the University here: Gothenburg Global Scholars. The Artistic Faculty consists of the departments HDK-Valand – Academy of Art and Design and Academy of Music and
-
chain, ranging from synthesis, cell assembly, characterization, modeling to scaled-up manufacturing. The 2-year postdoctoral project Machine Learning-based Electro-Chemo-Mechanical Estimation and Control
-
Do you want to contribute to the future of AI-driven electric transport systems? Join our research group to develop advanced machine learning methods for electromobility, focusing on energy-aware
-
of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
-
spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions
-
on lth.se . Subject and project description Wireless systems are becoming an increasingly important part of our everyday life. Using Machine Learning on measured wireless propagation channels as a means to
-
methods that combine soundscape targets, acoustic metamaterials, physical modelling, inverse design, machine learning and perceptual evaluation. The postdoc will develop models and design methods
-
machine learning for neuromorphic computing for predictive materials discovery. The doctoral student will be part of a larger project Brain-inspired AI Design of Topological Magnets for Sustainable