81 algorithm-development-"https:"-"Integreat--Norwegian-Centre-for-Knowledge-driven-Machine-Learning" positions in Sweden
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- Linköping University
- Lunds universitet
- SciLifeLab
- KTH Royal Institute of Technology
- Lulea University of Technology
- Umeå University
- KTH
- Linköpings universitet
- Umeå universitet stipendiemodul
- University of Lund
- Uppsala universitet
- Göteborgs Universitet
- IFM/Linköping University
- Jönköping University
- Karlstad University
- Karolinska Institutet, doctoral positions
- Luleå University of Technology
- Mälardalen University
- Nature Careers
- Sveriges Lantbruksuniversitet
- Umea University
- Umeå universitet
- Örebro University
- 14 more »
- « less
-
Field
-
, modulation classification, sensing, and adaptive spectrum optimization in diverse operational environments. Your work will focus on modeling and algorithmic aspects related to the development of highly
-
-driven, machine learning approaches. The biomass data product will be validated by data from an international network of ground-truth forest sites (GEO-TREES, geo-trees.org). The developed algorithms thus
-
logical perspectives. Key areas of interest include proof complexity, circuit complexity, communication complexity, meta-complexity, and their connections to algorithms. Lund University is located in
-
application! Your work assignments Spatio-temporal processes are everywhere in science and engineering, with applications ranging from weather prediction to cardiovascular medicine. Developing machine learning
-
will be as a researcher in a two-year project carried out in close collaboration with our industry partner. The goal is to develop methods for an ML-based decision support system for monitoring and fault
-
-year project carried out in close collaboration with our industry partner. The goal is to develop methods for an ML-based decision support system for monitoring and fault diagnosis of gas turbines
-
algorithmic aspects related to the development of highly accurate, efficient, and robust AI models capable of operating effectively within complex and dynamic radiofrequency spectral landscapes, accounting
-
mathematical theory and algorithm development as well as engineering methods that enable robust and efficient practical solutions. As society and technology evolve toward increasingly large‑scale, data‑intensive
-
will focus on developing theoretical and algorithmic foundations for goal-oriented, semantics-aware communication enabling timely and reliable cloud-to-agent interactions. For more details on semantic
-
the algorithmic capabilities of intelligent systems, reducing their computational costs, and bridging the gap between hardware and algorithm design. Duties and responsibilities The appointment as a postdoctoral