Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Linköping University
- Chalmers University of Technology
- Umeå University
- Stockholms universitet
- SciLifeLab
- Sveriges lantbruksuniversitet
- Lulea University of Technology
- Swedish University of Agricultural Sciences
- Uppsala universitet
- Nature Careers
- Umeå universitet
- University of Lund
- Lunds universitet
- Mälardalen University
- Chalmers University of Techonology
- Fureho AB
- KTH Royal Institute of Technology
- Linköpings universitet
- Linnaeus University
- Luleå University of Technology
- Mid Sweden University
- School of Business, Society and Engineering
- Stockholm University
- 13 more »
- « less
-
Field
-
”. This project research techniques for intelligently automating processes for large-scale simulation of robots and mobile machinery that operate in and physically manipulate dynamic environments. Research
-
electronic characteristics. The project’s goal is to develop fundamental understanding and innovative fabrication processes to solve urgent problems in organic electronic devices, and to enable new components
-
. Our group is fascinated by one of biology’s deepest questions: how does development—the process by which genes and environments build organisms—shape the potential for populations to evolve? We study
-
are, for example, novel food technologies, but also well-known food processing methods such as for example tofu and tempeh production using raw materials that can be domestically produced. The research will be based
-
SEEC, as well as to coordinate the processing, analysis, and presentation of surveillance data to the research community, stakeholders, and the general public. In addition, the role includes producing
-
to assimilate knowledge at the research level. Understanding and experience in machine learning and computer vision. Knowledge, experience, and strong interest and in AI and XR development. Knowledge and
-
. They involve high-stakes decisions with important trade-offs and uncertainties. They are also challenged by the data sampling process which gives rise to distribution shifts when comparing past and future data
-
novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities
-
cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities for practical impact by taking the outputs from the developed machine learning
-
derivatives to bio-chemicals on the anode side and simultaneously to generate green hydrogen in the cathode side. Subject description Energy engineering concerns the development of technologies and processes in