Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- UiT The Arctic University of Norway
- University of Stavanger
- NTNU Norwegian University of Science and Technology
- NORWEGIAN UNIVERSITY OF SCIENCE & TECHNOLOGY - NTNU
- NTNU - Norwegian University of Science and Technology
- Norwegian University of Life Sciences (NMBU)
- University of Bergen
- University of Oslo
- OsloMet – Oslo Metropolitan University
- Kristiania University College
- Norwegian University of Science and Technology (NTNU)
- OsloMet
- University of Agder
- University of Bergen (coordinating organisation)
- 4 more »
- « less
-
Field
-
knowledge for a better world. You will find more information about working at NTNU and the application process here. About the job For a position as a PhD Candidate, the goal is a completed doctoral education
-
31st July 2024 Languages English English English The Department of Engineering Cybernetics has a vacancy for a PhD Candidate PhD Candidate in Hybrid Machine Learning Apply for this job See
-
the utilization of experiment data. The two PhD positions will be complementary but have different focus: PhD position 1: This position will focus on micromechanics-based computational modelling of the stochastic
-
State regulations and guidelines at UiT. At our website, you will find more information for applicants . Remuneration for the position of PhD Fellow is in accordance with the State salary scale code 1017
-
. Desired qualifications experience with omics, big data, and statistics using R or similar tools good understanding of biological disease processes and ophthalmology experience using AI to predict health
-
guidelines at UiT. At our website, you will find more information for applicants . Remuneration for the position of PhD Fellow is in accordance with the State salary scale code 1017. A compulsory contribution
-
the utilization of experiment data. The two PhD positions will be complementary but have different focus: PhD position 1: This position will focus on micromechanics-based computational modelling of the stochastic
-
understanding of fundamentals in mathematics and physics. Competence on data processing and parsing, and an ability to work with large datasets. Experience with geographical information systems (e.g, through
-
detailed information on the admission criteria please see the PhD Regulations and the relevant PhD programme description . The applicant must document expertise and interest in the research subject. Required
-
previous studies and be able to document proficiency in both written and oral English. For more detailed information on the admission criteria please see the PhD Regulations and the relevant PhD programme