Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- KTH Royal Institute of Technology
- SciLifeLab
- Umeå University
- Chalmers University of Technology
- Karolinska Institutet (KI)
- Lunds universitet
- University of Lund
- Chalmers tekniska högskola
- Sveriges lantbruksuniversitet
- Swedish University of Agricultural Sciences
- Umeå universitet
- Chalmers
- Chalmers Tekniska Högskola AB
- Epishine
- Högskolan Väst
- Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg
- Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg
- Kungliga Tekniska högskolan
- Linköping University
- Linnaeus University
- Nature Careers
- Sveriges Lantbruksuniversitet
- Umeå universitet stipendiemodul
- University of Gothenburg
- Uppsala universitet
- Örebro University
- 16 more »
- « less
-
Field
-
with researchers at Chalmers and the University of Gothenburg. You will explore how Bayesian methods can enable risk-aware, real-time trajectory planning and contribute to the development of autonomous
-
University of Gothenburg. You will explore how Bayesian methods can enable risk-aware, real-time trajectory planning and contribute to the development of autonomous vehicles that are both safe and trustworthy
-
Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg | Sweden | 14 days ago
new knowledge and new perspectives, the University contributes to a better future. Doctoral position in Medical Science Project title: Modeling and targeting pacemaker cells in glioblastoma
-
Bayesian framework and two specific proposed lines of research: (1) constructing suitable priors via neural networks approximations, and (2) enhancing the sensitivity and efficiency of posterior diagnostics
-
presentation of analysis results. The ability to work with large and complex datasets. Excellent spoken and written English skills. Experience in machine learning, predictive modeling, and/or Bayesian methods
-
version control and containerization (Docker/Singularity) Statistical Modeling: Quantitative data analysis using GLMs, Bayesian methods, or mixed-effect models to interpret complex perturbation datasets
-
DHC Academy and the Hycogen 2 project. DHC Academy aims to develop an educational platform for district heating, targeting both practitioners and academics. The project is carried out in collaboration
-
-based, Bayesian or matrix factorization methods for multi-omics integration. Ability to independently perform data analysis and scientific interpretation based on omics data at an internationally
-
for district heating, targeting both practitioners and academics. The project is carried out in collaboration with several European universities and industry stakeholders. The Department of Energy Sciences
-
summaries, agentic workflows) to accelerate hypothesis generation and target prioritization. The role is collaborative and cross-disciplinary, interfacing with molecular biologists, bioinformaticians, and