Sort by
Refine Your Search
-
Listed
-
Employer
- Umeå University
- Uppsala universitet
- Chalmers University of Technology
- Linköping University
- Linköpings universitet
- University of Lund
- Sveriges lantbruksuniversitet
- Umeå universitet
- Chalmers University of Techonology
- Fureho AB
- KTH Royal Institute of Technology
- Luleå University of Technology
- Lunds universitet
- Nature Careers
- Stockholms universitet
- Swedish University of Agricultural Sciences
- 6 more »
- « less
-
Field
-
helping to build up an international research network and spending some time abroad at a relevant international university) Write single-authored and co-authored articles for publication in high-ranking
-
. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
-
and other team members in all aspects of the project. Be interested in internalization (e.g. by helping to build up an international research network and spending some time abroad at a relevant
-
networks (CNNs), which identify local correlations in the images. However, in this project, the aim is to go beyond standard CNN-based methods by developing new approaches based on transformers, and implicit
-
receive the benefits of support in career development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available
-
-native networks or financial services, AI/ML that is not secure, robust, verifiable, or privacy-preserving can lead to safety risks, regulatory violations, and significant reputational damage. By making AI
-
. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material
-
Gionis. The position is part of the European project ARMADA funded by the Marie-Skłodowska-Curie Doctoral Network. The ARMADA project operates within the fast-growing field of Conversational AI, aiming
-
should do it — with high assurance. Our project aims to integrate Linear Temporal Logic (LTL) and the Planning Domain Definition Language (PDDL) to build a more expressive and efficient framework
-
following years. Your work will be guided by experienced researchers in your advisory group, but you will also benefit from the broad range of competences and networks of the full ANAFOR team. Qualifications