141 model-driven-development "Integreat Norwegian Centre for Knowledge driven Machine Learning" Postdoctoral positions in Sweden
Sort by
Refine Your Search
-
Listed
-
Employer
- Chalmers University of Technology
- KTH Royal Institute of Technology
- Umeå University
- University of Lund
- Lunds universitet
- SciLifeLab
- Karolinska Institutet (KI)
- Swedish University of Agricultural Sciences
- Mälardalen University
- Linköping University
- Luleå tekniska universitet
- The Swedish University of Agricultural Sciences
- Umeå universitet stipendiemodul
- Uppsala universitet
- Blekinge Institute of Technology
- Lulea University of Technology
- Luleå University of Technology
- Uppsala University
- Institutionen för biologi och miljövetenskap
- Jönköping University
- Karlstad University
- Linköping University (LiU)
- Sveriges Lantbruksuniversitet
- University of Borås
- University of Skövde
- 15 more »
- « less
-
Field
-
research environments in Computational Science, the research and education has a unique breadth, with large activities in areas such as numerical analysis, mathematical modelling, development and analysis
-
geoinformatics and spatial data science, including demonstrated knowledge of GIS, spatial analysis, spatial modelling, and GeoAI. Experience and expertise in WebGIS development, familiar with the core technologies
-
and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
-
and variation. The successful candidate will develop innovative methods and models to advance our understanding of genome evolution and variation. The position is based in the Computational Genomics
-
development of the project. We are particularly interested in candidates whose background can help us connect empirical mobility data and computational modelling with theories of complex systems, network
-
to 2 postdoctoral researchers on technology foresight for policy-driven low-carbon technologies. The postdoctoral position will focus on developing data-driven approaches for probabilistic modelling
-
of engagement. Read more at: Department of Computing Science Project description and working tasks The project will develop privacy-aware machine learning (ML) models. We are interested in data-driven
-
biologists to test model predictions, and the motivation to develop their skills at the intersection of quantitative modelling, cell biology, and algal biochemistry. Experience in parameter fitting
-
. Project description This project will respond to the increasingly large-scale and heterogeneous data of the social and behavioural sciences by developing a new generation of latent variable models
-
largest laboratories with ultramodern facilities and rich opportunities for collaboration and career development. Division Our lab is interested in stimulating regeneration in the mammalian central nervous