Sort by
Refine Your Search
-
Listed
-
Employer
- University of Lund
- Chalmers University of Technology
- Nature Careers
- Linköping University
- Lulea University of Technology
- SciLifeLab
- KTH Royal Institute of Technology
- Linnaeus University
- Swedish University of Agricultural Sciences
- Umeå University
- Karolinska Institutet (KI)
- Luleå University of Technology
- Lunds universitet
- Mälardalen University
- Umeå universitet stipendiemodul
- 5 more »
- « less
-
Field
-
collaborate with multiple stakeholders and conduct applied research in silviculture, forest ecology, pathology, policy and planning. We teach bachelor, Masters and PhD level courses addressing all
-
expertise. In addition, Uppsala University has a highly developed innovation office that gives support for commercialization and external collaboration. Read more here. Uppsala University offers one
-
commitment to lifelong learning. The department emphasizes strong collaboration between academia, industry, and society, with a clear focus on utilisation. M2 is characterised by an international environment
-
laureate Emmanuelle Charpentier, who discovered the CRISPR-Cas9 gene editing technology during her time as a scientist and group leader in Umeå. The ‘EC’ Postdoctoral fellow will: Develop a collaborative
-
learning approaches. Consideration will also be given to good collaborative skills, drive and independence, and how the applicant’s experience and skills complement and strengthen ongoing research within
-
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
-
include the design and implementation of finite element multiscale models and machine learning algorithms, analyzing related experimental data, and collaborating with industrial collaborators to validate
-
based on the Arctic region, we create global social benefit. Our scientific and artistic research and education are conducted in close collaboration with international, national and regional companies
-
on collaboration and trust, where development towards an independent researcher is largely encouraged and supported. The research is connected to the LTH profile area Engineering Health. More information about the
-
-scale computational methods, and bioinformatics. The division is also expanding in the area of data science and machine learning. Our department continuously strives to be an attractive employer. Equality