Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oslo
- University of Bergen
- University of South-Eastern Norway
- Western Norway University of Applied Sciences
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- University of Stavanger
- NTNU - Norwegian University of Science and Technology
- UiT The Arctic University of Norway
- University of Agder
- University of Inland Norway
-
Field
-
power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
-
to calculate your points for admission. Emphasis is also placed on your: background in algebraic or symplectic geometry or mathematical physics programming skills and experience with computer algebra packages
-
Experience with high-throughput sequencing omics data analysis Proficiency in programming with Python, R, or C++ Desired: Familiarity with statistical and machine learning techniques. Knowledge about molecular
-
, or C++ Desired: Familiarity with statistical and machine learning techniques. Knowledge about molecular biology and/or gene regulation. Experience with nanopore sequencing, Hi-C, ribosome profiling
-
or more of the following empirical research methods will be considered an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the
-
application”. If you do not already have educational competence that meets the requirements for a position as associate professor in Norway, NTNU will arrange for you to acquire such competence during
-
addressing measurement quality issues related to respondent non-compliance in ecological momentary assessment, or exploring the use of machine learning techniques to aid the estimation of item response theory
-
at https://cbu.w.uib.no/joshi-group/ . Co-supervisors include experts in machine learning and AI, Pekka Parviainen and Tom Michoel, alongside leading epidemiologists, Tone Bjørge and Kari Klungsøyr. The core
-
. The HDL and SPKI research groups are part of the Centre of Research-based Innovation SFI Visual Intelligence that is a center-of excellence in machine learning research. The research groups are also active
-
well as for validation of numerical simulation results. As part of the work task, we expect machine learning to be employed to improve accuracy and efficiency of numerical methods, combining advanced technology with