Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
-
Field
-
disease prognosis. This position offers a unique opportunity to work at the forefront of optical imaging technology, combining experimental optics with advanced computational and data-driven methods. Roles
-
, supporting studies on ulcer disease prognosis. This position offers a unique opportunity to work at the forefront of optical imaging technology, combining experimental optics with advanced computational and
-
8 Feb 2026 Job Information Organisation/Company University of Oslo Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 1 Mar
-
no later than October 1, 2026. No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. The position is placed in the Digital Signal Processing and Image Analysis
-
UiO/Anders Lien 1st March 2026 Languages English English English PhD Research Fellow in Deep learning for imaging of marine ecosystems Apply for this job See advertisement About the position
-
modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department
-
digital signal processing and acoustic imaging. The group includes around 20 postdoctoral researchers and PhD research fellows funded by a range of national and international agencies, as well as from
-
ecosystems Apply for this job See advertisement About the position Position as PhD Research Fellow in Deep learning for imaging of marine ecosystems available at the Department of Informatics. Starting date as
-
UiO/Anders Lien 5th April 2026 Languages English English English PhD Research Fellow in Theoretical and Computational Active Matter Physics Apply for this job See advertisement About the position A
-
Fellow in Deep learning for subsurface imaging Apply for this job See advertisement About the position Position as PhD Research Fellow in Deep learning for subsurface imaging available at Department