Sort by
Refine Your Search
-
Category
-
Program
-
Employer
- SciLifeLab
- Chalmers University of Technology
- Umeå University
- University of Lund
- KTH Royal Institute of Technology
- Blekinge Institute of Technology
- Lulea University of Technology
- Uppsala universitet
- Jönköping University
- Luleå University of Technology
- Linköping University
- Lunds universitet
- University of Skövde
- Helmholtz-Zentrum München
- Karlstad University
- Karolinska Institutet (KI)
- Karolinska Institutet, doctoral positions
- Linköping University (LiU)
- Linnaeus University
- Swedish University of Agricultural Sciences
- The Swedish University of Agricultural Sciences
- The University of Skövde
- Umeå universitet
- Uppsala University
- universitypositions
- 15 more »
- « less
-
Field
-
modeling of protein dynamics We are seeking a highly motivated PhD student to join a DDLS-funded project at the interface of structural proteomics, protein biophysics, and machine learning. The position is
-
spans computational materials design, catalysis, energy materials, machine learning, and artificial intelligence. We offer a collaborative and international research environment with close interactions
-
to knowledge in one or more of the following areas: machine learning, cybersecurity, or computer systems Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in
-
Do you want to contribute to the future of AI-driven electric transport systems? Join our research group to develop advanced machine learning methods for electromobility, focusing on energy-aware
-
or heterogeneous environmental datasets Familiarity with spatial analysis, GIS, or geospatial data workflows. Experience with machine learning, modelling, or systems analysis approaches Interest in resilience
-
nutrition, such as: analysis of time series data and dynamic processes, where signals and responses evolve over time. statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and
-
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
-
in English (reading, writing, speaking). • Show ability to work independently as well as in a team. • Good knowledge in AI, machine learning, data science and mathematics. • Good knowledge in one
-
software or similar languages and experience with modern machine learning and deep learning frameworks parallel computing using clusters like UPPMAX and GPUs for high-performance computing and parallel
-
and application of AI/machine learning methods and statistical modelling for the analysis of biological and medical data. Demonstrated ability to communicate and present scientific research findings in