Sort by
Refine Your Search
-
Listed
-
Employer
- Umeå University
- Linköping University
- Sveriges lantbruksuniversitet
- Swedish University of Agricultural Sciences
- Uppsala universitet
- Chalmers University of Technology
- Lulea University of Technology
- SciLifeLab
- University of Lund
- Mälardalen University
- Nature Careers
- Stockholms universitet
- Luleå University of Technology
- Lunds universitet
- Umeå universitet
- Chalmers University of Techonology
- Chalmers tekniska högskola
- Fureho AB
- Institutionen för biomedicinsk vetenskap
- KTH Royal Institute of Technology
- Karolinska Institutet, doctoral positions
- Linköpings universitet
- Mälardalens universitet
- School of Business, Society and Engineering
- 14 more »
- « less
-
Field
-
programming Merits: Experience in modelling erosion problems Understanding of critical state soil mechanics, elasto-plastic and elasto-viscoplastic models Experience in numerical analyses (using finite elements
-
Chemistry (experimental/computational physical chemistry) -Transition metal photocatalysts studied by femtosecond X-ray science with a focus on hybrid experimental/machine-learned structural dynamic analyses
-
funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you interested in working with machine learning methods with the support of
-
approaches that combine artificial intelligence, machine learning, natural language processing, and social sciences. This collaborative and cross-sectoral approach aims to produce robust methods for evaluating
-
department is available at: https://www.umu.se/en/department-of-computing-science/ Project description Graph transformation is a well-established theory that studies computational methods to transform graphs
-
Artificial Intelligence.” The project aims to develop and empirically validate a taxonomy of non-ordinary states of consciousness (NOS) using artificial intelligence and language technology methods. The focus
-
to study gene function in malaria parasites. The PhD student will apply scalable and innovative analytical methods to characterize the role of parasite genes during replication and host interactions
-
flow, fluid dynamics, and sustainable energy systems. The research focuses on developing new methods to study and model multiphase flows as key phenomena in energy and industrial processes. The work
-
on developing a fundamental understanding and numerical models for multiphase flows, which are crucial for various industrial processes. The successful candidate will develop advanced physics-based methods in
-
independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical skills. Throughout