Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- Chalmers University of Technology
- SciLifeLab
- KTH Royal Institute of Technology
- Umeå University
- University of Lund
- Blekinge Institute of Technology
- Lunds universitet
- European Magnetism Association EMA
- Karolinska Institutet (KI)
- Lulea University of Technology
- Luleå University of Technology
- Umeå universitet stipendiemodul
- Uppsala universitet
- 3 more »
- « less
-
Field
-
challenges in the machine learning domain, e.g., complexity of machine learning algorithms, reliability, and trust. An important part of your work will be to develop the theoretical foundation of trustworthy
-
develop algorithms for this purpose. The group collaborates with several national and international research groups, edits one of the major journals on data privacy (Transactions on Data Privacy), and has
-
learning tools and algorithms. The position will also require you to contribute to the development of data-driven methods. The nature of LDMX as an international project will require you to work
-
possible. One or two extended research visits are encouraged during the doctoral study. Applicants should have a strong interest in the mathematical analysis of algorithms in general and cryptography in
-
out together with seven industrial partners and is externally funded by the Knowledge Foundation. In co-production with our corporate partners and the community, we develop concepts, principles, methods
-
in the presence of strategic, realistically constrained adversaries and probabilistic uncertainty. We seek to develop analysis and design algorithms that incorporate cross-layer information and account
-
investigate suitable topologies, materials, and components to achieve high efficiency and scalability up to 500 kW. Advanced control algorithms will be developed to ensure stable power flow under varying
-
or communications venues. Interest in mission-critical and critical infrastructure scenarios. What you will do Develop models, algorithms and optimization methods for resilient 6G transport networks, using machine
-
or communications venues. Interest in mission-critical and critical infrastructure scenarios. What you will do Develop models, algorithms and optimization methods for resilient 6G transport networks, using machine
-
Are you interested in developing mathematically grounded methods for uncertainty quantification in deep learning, particularly for large language models in healthcare applications? Are you looking