65 machine-learning "https:" "https:" "https:" "https:" "https:" positions at University of Oslo
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
, in close collaboration with the machine learning group at the Department of Informatics, both at University of Oslo. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs
-
researchers and PhD students. The research groups conduct research in various areas of mobile network systems, multimedia and AR/VR/XR systems, robotics and machine learning, focusing on fundamental aspects as
-
separation on commercial recordings and extracting audio features (onsets, pitch, harmony, dynamics); curating datasets; and integrating machine learning approaches to complement rule-based methods. For more
-
for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
-
-in-machine-learning-for-cognitive-neuroscience Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294553/phd-research-fellow-in-ma… Requirements Research FieldComputer
-
: https://www.jobbnorge.no/en/available-jobs/job/294558/phd-research-fellow-in-deep-learning-for-imaging-of-marine-ecosystems Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/294558/phd
-
of the researchers of the DKM group are also affiliated with the Norwegian Centre for Knowledge-driven Machine Learning (Integreat) . The candidate is expected to join Integreat and strengthen the interdisciplinary
-
topics such as statistics, high performance programming, machine learning and using data to constrain cosmological models. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs
-
developed countries, smartphone penetration exceeds 80%. The automatic transport mode detection (TMD), when effectively exploited, possibly using some kind of machine learning algorithm, provides more
-
to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide