Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oslo
- UiT The Arctic University of Norway
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of South-Eastern Norway
- CMI - Chr. Michelsen Institute
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- OsloMet
- University of Agder
- University of Bergen
-
Field
-
20th May 2026 Languages English English English The Department of Computer Science has a vacancy for a Postdoctoral Fellow in System-Level Analysis of Deep-Learning Acceleration Apply for this job
-
to work on cutting-edge research at the intersection of deep learning and computer systems. The successful candidate will join an international and collaborative research environment and contribute
-
and accelerate the development of more high-performing PNSEs. The ultimate goal of the project is to develop, implement, and validate novel deep-learning models for molecular dynamics and coarse-grained
-
functions to work properly. Please turn on JavaScript in your browser and try again. UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Deep learning for imaging of marine
-
UiO/Anders Lien 9th February 2026 Languages English English English Join a vibrant team at the University of Oslo as a PhD Research Fellow in Deep Learning for geoscience imaging! PhD Research
-
Is the Job related to staff position within a Research Infrastructure? No Offer Description You are keen on contributing to new advances in deep learning methodology for imaging for monitoring marine
-
, as well as from industry. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/294560/phd-research-fellow-in-deep-learning-for-medical-imaging-and-multi-modal-data-in
-
Learning for Medical Imaging and Multi-Modal Data in Cancer Research Apply for this job See advertisement About the position Position as PhD Research Fellow in Deep Learning available at the Department
-
models • Strong experience in spatio-temporal deep learning and ensemble techniques • Proven ability to publish research in international peer-reviewed journals • Experience with interdisciplinary
-
, and who are eager to contribute to impactful methods for generating private and fair synthetic data with good utility. This project involves development of deep learning based synthetic data generators