Sort by
Refine Your Search
-
Listed
-
Employer
- Linköping University
- Stockholms universitet
- Lulea University of Technology
- Mälardalen University
- Umeå University
- Uppsala universitet
- Chalmers University of Technology
- Chalmers University of Techonology
- Linkopings universitet
- Linköpings universitet
- School of Business, Society and Engineering
- Stockholm University
- Sveriges lantbruksuniversitet
- 3 more »
- « less
-
Field
-
, implementation of methods in computer codes, use of state-of-the-art high-performance computers in Sweden and in Europe, application of machine-learning and AI techniques, and collaborations with leading
-
flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
-
facilitate data sharing among actors involved in a new circular flow of flat glass. Within the project, two PhD students, one at the Department of Computer and Information Science (with computer
-
combines: Fluid dynamics and heat transfer (theory and experiments), Computational modeling, and Machine learning / computer vision for data analysis and pattern recognition. The goal is to improve
-
collaboration with the Materials Design Division (also at IFM) and with the Computer Vision Laboratory at the Department of Electrical Engineering (ISY), a world-class research environment specializing in
-
) and with the Computer Vision Laboratory at the Department of Electrical Engineering (ISY), a world-class research environment specializing in machine learning, deep learning, and visual perception
-
-ray computer tomography. The position will be open at the Fluid Dynamic division of Mechanical and Maritime Science department. The research at the Division covers turbulent flow (both compressible and
-
multiphase flow behavior. The project also involves applying machine learning and computer vision techniques to enhance data analysis, pattern recognition, modeling, and prediction. The role requires a solid
-
or more (with none of the sections scoring less than 5.0) • TOEFL score of 550 or more (computer based test 213, internet based 79) • Cambridge/Oxford - Advanced or Proficiency level. Selection
-
English IELTS score (Academic) of 6.0 or more (with none of the sections scoring less than 5.0) TOEFL score of 550 or more (computer based test 213, internet based 79) Cambridge/Oxford - Advanced