Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- NTNU - Norwegian University of Science and Technology
- Nord University
- UiT The Arctic University of Norway
- University of Bergen
- University of Oslo
- Norwegian University of Life Sciences (NMBU)
- Østfold University College
- NHH Norwegian School of Economics
- Norwegian Institute of International Affairs
- Norwegian Meteorological Institute
- SINTEF
- University of Oxford
- 2 more »
- « less
-
Field
-
properly. Please turn on JavaScript in your browser and try again. 13th June 2025 Languages English English English PhD candidate in Statistics at the Oslo Centre for Biostatistics and Epidemiology (OCBE
-
, Robotics, Computer Science, Statistics, or related discipline. Strong background in Machine Learning and Control Theory. Demonstrated experience in research projects with industrial partners. Excellent
-
, pharmacoepidemiology, public health, statistics or a related field. The position offers excellent opportunities for scientific development within an international research environment. About the project/work tasks The
-
motivated candidate with a background in neuropsychology, medicine, neuroscience, molecular biology, biostatistics, pharmacology, pharmacoepidemiology, public health, statistics or a related field. The
-
epidemiology, causal inference, genetic epidemiology, and machine learning. As a PhD candidate in the project, you will: Actively participate in group meetings, design statistical analysis plans in collaboration
-
Vibration from 2026 on. The Acoustics Group at NTNU works closely with the SINTEF Acoustics Research Group on the campus of Gløshaugen. This represents a workforce of 30 researchers, professors, postdocs
-
degree (or equivalent) in biology, bioinformatics, genetics, molecular ecology, or a related field. A good knowledge and practical experience in molecular ecology, population genetics, and statistical and
-
-on experience in benthic ecology and statistical analysis are required. Additional experience in analysing biodiversity data, ship-based sampling, marine plankton (preferably meroplankton), handling and analysing
-
(or equivalent) in biology, bioinformatics, genetics, molecular ecology, or a related field. Solid knowledge and practical experience in molecular ecology, population genetics, and statistical and bioinformatic
-
species and vegetation ecology), advanced statistical modelling using R software, and conducting fieldwork under harsh environmental conditions. A successful applicant should have good skills in English and