Sort by
Refine Your Search
-
Listed
-
Program
-
Employer
- Chalmers University of Technology
- Linköping University
- Umeå University
- Jönköping University
- SciLifeLab
- Umeå universitet
- University of Lund
- Faculty of Technology and Society
- IFM/Linköping University
- Karlstad University
- Linköpings universitet
- Lulea University of Technology
- Luleå University of Technology
- Mälardalen University
- Nature Careers
- Sveriges Lantbruksuniversitet
- Umeå universitet stipendiemodul
- Uppsala universitet
- 8 more »
- « less
-
Field
-
, experience working with the PyTorch framework, documented ability to develop algorithms and implement them in efficient code, and experience in statistical modeling, optimization or numerical methods, as
-
, algorithms, data or automation affect the public sector, preferably from a critical perspective. Assessment criteria This is a career development position primarily focused on research. The position is
-
Are you interested in developing machine learning algorithms that provably help us make better decisions? Join us as a post-doc in the Division of Data Science and AI, Department of Computer Science
-
imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring
-
research within Unmanned Traffic Management (UTM). In this role, your primary responsibility will be the hands-on development of advanced simulations and prototypes that help us test and validate new UTM
-
they can contain traces of the data used in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose
-
of the data used in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with
-
Biochemistry advances multiphase flow and separation science to accelerate industrial innovation and implementation. About the research project The project aims to develop hybrid quantum–classical approaches
-
knowledge and fosters the development of highly skilled researchers and professionals. Our research focuses on material properties and manufacturing processes for mainly metallic components, specifically cast
-
multidisciplinary research and education environment that advances the state-of-the-art knowledge and fosters the development of highly skilled researchers and professionals. Our research focuses on material