Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- University of Oslo
- NTNU - Norwegian University of Science and Technology
- NTNU Norwegian University of Science and Technology
- University of Bergen
- Norwegian University of Life Sciences (NMBU)
- UiT The Arctic University of Norway
- University of Agder
- University of South-Eastern Norway
- Norwegian Institute of Bioeconomy Research
- UNIS
- Molde University College
- Oslo University Hospital
- Oslo University Hospital (OUS)
- University of Stavanger
- 4 more »
- « less
-
Field
-
to the faculty's Doctoral Programme (https://www.ntnu.no/studier/phma ). You must have documented programming experience relevant to scientific computing, for example in Python, MATLAB, Julia, C++ or similar
-
/phma ). Applicants must have significant programming experience ideally in C, C++, R and/or Python. You must have good written and oral communication skills in English. PLEASE NOTE: For detailed
-
to the faculty's Doctoral Programme (https://www.ntnu.no/studier/phma ). Applicants must have significant programming experience ideally in C, C++, R and/or Python. You must have good written and oral
-
skills will be considered an advantage: Natural Language Processing; LLMs; R; Python. Experience with teaching and supervision will be considered an advantage. Very good skills in Norwegian or other
-
://www.ntnu.no/studier/phma ). Applicants must have significant programming experience ideally in C, C++, R and/or Python. You must have good written and oral communication skills in English. PLEASE NOTE: For
-
to the faculty's Doctoral Programme (https://www.ntnu.no/studier/phma ). You must have documented programming experience relevant to scientific computing, for example in Python, MATLAB, Julia, C++ or similar
-
in Python, Julia, Matlab, R or similar languages GIS-based spatial analysis and/or geospatial data processing Knowledge of energy justice, or sustainability transitions Familiarity with renewable
-
needed to be admitted to the PhD programme. Experience with data statistical analyses including knowledge of R and/or python. Experience in biodiversity- and/or ecological studies in aquatic environments
-
, such as longitudinal data, registry data, electronic health records, cohort data or trial data. Strong programming skills in R, Python or equivalent scientific computing languages. Strong R skills
-
material flow analysis, ecological risk assessment, social impact assessment. Competences in python programming. Personal characteristics To complete a doctoral degree (PhD), it is important that you are