Sort by
Refine Your Search
-
Listed
-
Employer
- KTH Royal Institute of Technology
- Chalmers University of Technology
- Lunds universitet
- SciLifeLab
- Umeå University
- University of Lund
- Karolinska Institutet (KI)
- Umeå universitet stipendiemodul
- Uppsala University
- Blekinge Institute of Technology
- Institutionen för biologi och miljövetenskap
- Linköping University
- Luleå University of Technology
- Luleå tekniska universitet
- The Swedish University of Agricultural Sciences
- University of Skövde
- Uppsala universitet
- 7 more »
- « less
-
Field
-
KTH Royal Institute of Technology, School of Engineering Sciences Job description The AICell Lab (https://aicell.io ) in the department of Applied Physics at KTH and Science for Life Laboratory is a
-
. Location: Gävlegatan 22, Torsplan, Stockholm/Solna Learn more about KIND here Choose to work at KI – Ten reasons why Application An application must contain the following documents in English or Swedish: * A
-
on development of novel computational methods with state-of-the-art machine learning for gaining fundamental insights into healthy and diseased human tissues of the heart, cardiovascular system, and
-
the Uppsala University application system VARBI: https://uu.varbi.com/en/what:login/type:job/jobID:915373 The Department of Physics and Astronomy at Uppsala University, Sweden has an opening for a two-year
-
dynamics & control, developing systems that push the boundaries of robotic locomotion. Learn more at chalmers-rail.github.io . About the research project Free-standing passengers on public transport – buses
-
, drawing on machine learning where it strengthens these methods. The research supports mission-critical scenarios and feeds into an end-to-end resilience proof of concept developed together with Swedish and
-
. For more information about the Akelius Math Learning Lab, see: https://www.chalmers.se/institutioner/mv/akelius-math-learning-lab/ Who we are looking for The following requirements are mandatory: Doctoral
-
. The position includes the opportunity for three weeks of training in higher education teaching and learning. The purpose of the position is to develop the independence as a researcher and to create
-
infrastructure, mobility demand, and power grid operations. On top of this environment, a deep-learning-based learning will be developed to enable decentralized and coordinated decisions on EV user charging
-
candidates whose expertise falls within one or more of the following areas: computational and mathematical modeling, statistical modeling, machine learning, network science, bioinformatics, applied mathematics