Sort by
Refine Your Search
-
Listed
-
Employer
- University of Lund
- Chalmers University of Technology
- Nature Careers
- Umeå University
- Swedish University of Agricultural Sciences
- Linköping University
- Lulea University of Technology
- Linnaeus University
- SciLifeLab
- Jönköping University
- KTH Royal Institute of Technology
- Karolinska Institutet (KI)
- Lunds universitet
- Mälardalen University
- Umeå universitet stipendiemodul
- Luleå University of Technology
- Sveriges lantbruksuniversitet
- Uppsala universitet
- 8 more »
- « less
-
Field
-
Description of the workplace The position is based at Lund University’s Faculty of Medicine, within the Department of Experimental Medical Sciences, specifically the Medical Structural Biology
-
developing a novel imaging and amperometry-based platform for research into neurological diseases. About us The Esbjörner lab belongs to the Division of Chemical Biology , which is part of the Department
-
education and to the educational programmes at MDU. A broad range of topics and perspectives are thereby possible (workplace-based learning, simulation in professional education, student characteristics etc
-
to solving applied problems through research, collaboration and education on sustainable plant production. We teach and research plants for food, feed and energy. The research and teaching focus
-
facility belonging to SciLifeLab, part of a national infrastructure for research in life science. The creative and research-intense environment contributes to a broad knowledge-base as well as cutting-edge
-
classification and multi-layered environment mapping -Digital twin generation for natural environments -Semantic scene-understanding in natural environments for robust decision-making -Learning-based
-
on LLM-based risk analysis and demonstrate its applications in various risk control measures. You will collaborate closely with other researchers at the division and contribute to building a shared
-
University is offering a postdoctoral scholarship within optical metrology linked to machine learning. The postdoctoral scholarship is full-time 6 months, beginning on October 15 , 2025, or as agreed upon
-
great advantage: Forest and wood production processes Wood construction Furniture manufacturing Wood material science Machine learning Process simulation and optimisation The postdoctoral fellow is part
-
. Deep understanding of analysis data from XRF, XRD, BET, ICPMS, LA-ICPMS. Additionally meritorious: Being well acquainted with safety aspects specific to the work (high temperatures and CaO-based