Sort by
Refine Your Search
-
Employer
- Chalmers University of Technology
- Chalmers tekniska högskola
- Karolinska Institutet (KI)
- Luleå University of Technology
- KTH Royal Institute of Technology
- Linköping University
- Nature Careers
- Sveriges lantbruksuniversitet
- Umeå University
- Linköpings University
- SciLifeLab
- Swedish University of Agricultural Sciences
- 2 more »
- « less
-
Field
-
monitoring. The position is planned to start in January 2026. About us At the Department of Electrical Engineering (E2), we conduct internationally recognized research across multiple areas, including
-
experiments (both in the lab and in the field), coordinating cross-cultural studies involving multiple international research groups, data analysis, computational modeling, and writing scientific articles
-
improving material and energy systems across multiple applications, including: High-temperature corrosion prevention Development of advanced fuel cells Recycling of valuable materials Innovations in nuclear
-
LiDAR and UAV photogrammetry) with physiological and spectral indicators of forest health. The research will be conducted at multiple spatial scales, from single trees to landscapes, and integrated
-
of working effectively both independently and as part of a multidisciplinary team. Organized: Excellent organizational skills, capable of managing multiple tasks and projects effectively. Excellent
-
LiDAR and UAV photogrammetry) with physiological and spectral indicators of forest health. The research will be conducted at multiple spatial scales, from single trees to landscapes, and integrated
-
fundamental research in robotics autonomy with a strong European and National participation in multiple R&D&I projects. RAI has participated in the DARPA SUB-T challenge with the CoSTAR Team lead by NASA/JPL
-
search and rescue, multi sensorial fusion and multirobot coordination, including multirobot perception, decentralization and mission execution. The RAI team has a strong European participation in multiple
-
mathematics, ecology, history, climatic and medical sciences in collaboration across multiple institutes. An integral part of the project is to develop process-based eco-epidemiological models considering