Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Karolinska Institutet (KI)
- Umeå University
- Umeå universitet
- University of Borås
- Chalmers tekniska högskola
- Linköpings University
- Luleå University of Technology
- Lunds universitet
- Malmö universitet
- Nature Careers
- SciLifeLab
- University of Lund
- Örebro University
- 5 more »
- « less
-
Field
-
Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Description of the workplace You will be working at the Department
-
the capabilities of fully digital Large Intelligent Surfaces. Subject description The research subject for this position is development of distributed processing strategies and algorithms for Large Intelligent
-
deemed equivalent in Computer Science, or another subject of relevance for the project. Documented knowledge and proven research experience in the area of designing algorithms and methods for data privacy
-
, or as agreed upon. The Department of Computing Science has been growing rapidly in recent years, with a focus on creating an inclusive and bottom-up driven research environment. Our workplace consists
-
, robotics, machine learning, and human-robot interaction. Subject area The subject area for this position is Computer Science. Background The focus of the project is artificial intelligence (AI) and its
-
8 Nov 2025 Job Information Organisation/Company KTH Royal Institute of Technology Research Field Computer science » Other Engineering » Electrical engineering Engineering » Other Technology
-
7 Nov 2025 Job Information Organisation/Company University of Borås Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions Other Positions Country Sweden
-
environment. Qualifications Specific requirements for this position: A bachelor's degree or master's degree in computer science or related topics A strong understanding of machine learning algorithms, deep
-
, computer science, physics, materials science, or related fields. You must have proven expertise in at least one of the following fields: computational geometry, algorithm development, machine learning
-
Networks (DAS)". The work includes: design and implementation of RL algorithms to address the challenges of peak load variations in district heating systems development and use of simulation models