Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- University of Lund
- Umeå University
- Lunds universitet
- Karolinska Institutet (KI)
- SciLifeLab
- Swedish University of Agricultural Sciences
- Linköping University
- Umeå universitet stipendiemodul
- Blekinge Institute of Technology
- Lulea University of Technology
- Luleå tekniska universitet
- Mälardalen University
- The Swedish University of Agricultural Sciences
- Karlstad University
- Luleå University of Technology
- Umeå universitet
- Institutionen för biologi och miljövetenskap
- Jönköping University
- Linköping University (LiU)
- Sveriges Lantbruksuniversitet
- The Royal Institute of Technology (KTH)
- University of Borås
- University of Skövde
- Uppsala University
- Uppsala universitet
- universitypositions
- 18 more »
- « less
-
Field
-
/JPL (https://costar.jpl.nasa.gov/ ). Subject description Robotics and artificial intelligence aim to develop novel robotic systems that are characterized by advanced autonomy for improving the ability
-
/JPL (https://costar.jpl.nasa.gov/ ). Subject description Robotics and artificial intelligence aim to develop novel robotic systems that are characterized by advanced autonomy for improving the ability
-
, which provides a great opportunity to be involved in challenging development projects. Qualifications To be qualified for the position, you must hold a PhD degree in Control Engineering, Computer
-
Postdoctoral Fellow (2022-02-01)”. The start date is 1 November 2026, or as otherwise agreed. Eligibility To be eligible for employment as a postdoctoral researcher, the applicant must have been awarded a PhD
-
the opportunity for three weeks of training in higher education teaching and learning. The job also includes opportunities for teaching on basic and advanced level. participation in supervision of master and PhD
-
A PhD in economics, or agricultural economics, or a closely related field must be completed before the start of the position. If the PhD has not yet been completed at the time of application
-
regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
-
researcher who has a strong background in natural sciences including freshwater sciences. The candidate should have a PhD in natural sciences (e.g., ecology, physical geography, forestry), ideally with
-
work and documentation and presenting data, results and method development internally and externally, both in written and oral presentations Supervise master’s and/or PhD students to a certain extent
-
collaborate closely with the project team, including co-supervising the project's PhD student and working with partners at the University of Texas at Austin. In terms of study area, you will primarily focus