Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- Nature Careers
- Umeå University
- Karolinska Institutet (KI)
- Linköping University
- Linnaeus University
- KTH Royal Institute of Technology
- Umeå universitet stipendiemodul
- Luleå University of Technology
- Chalmers tekniska högskola
- Jönköping University
- Linneuniversitetet
- Lulea University of Technology
- Mälardalen University
- SciLifeLab
- Sveriges lantbruksuniversitet
- Swedish University of Agricultural Sciences
- 7 more »
- « less
-
Field
-
the Competence Centre for Catalysis (KCK) and the Chalmers Area of Advance Energy, which provide strong networks and resources for your research. Project overview The project aims to explore new catalytic
-
research, often in collaboration with industrial partners. The project is part of the Competence Centre for Catalysis (KCK) and the Chalmers Area of Advance Energy, which provide strong networks and
-
the department’s environment and networks, both internally and externally Qualifications A doctorate in mathematics or another field relevant to the assessment criteria below, or possesses an equivalent degree from
-
Close collaborations with the New York Genome Center and with the infrastructure platforms at SciLifeLab An opportunity to develop an internationally competitive research profile and networks as
-
activities aiming at developing soft skills and at strengthening networks and collaborations in academia and industry. Be part of a strong postdoc community. The Umeå Postdoc Society fosters networking and
-
architecture and forest structure analysis. We expect you to develop innovative research and report findings in high-impact scientific journals. We expect you to network and collaborate with remote sensing
-
and flexible work environment, with opportunities for collaboration and networking both within Chalmers and internationally. Chalmers is an employer that actively promotes equal opportunities for women
-
will have the opportunity to collaborate with the strong multi-disciplinary and international professional network between researchers and industry associated with the WASP. The RAI team conducts
-
experience with interdisciplinary research networks, and a record of successfully attracting external funding for interdisciplinary research projects. To be able to use computationally intensive methods
-
required. Proficiency in statistics and programming are highly meriting, especially in gene regulatory networks, machine learning, and bioinformatics tools. Expertise in CRISPR-based assays, especially