Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Umeå University
- SciLifeLab
- Swedish University of Agricultural Sciences
- Linköping University
- University of Lund
- Lulea University of Technology
- Lunds universitet
- Uppsala universitet
- Luleå University of Technology
- Blekinge Institute of Technology
- Chalmers University of Technology
- Göteborgs universitet
- Institute of Neuroscience and physiology, Sahlgrenska Academy, university of Gothenburg
- Institutionen för Biologi och miljövetenskap
- Institutionen för mark och miljö
- Karolinska Institutet, doctoral positions
- Linnaeus University
- Mälardalen University
- Sveriges Lantbruksuniversitet
- Sveriges lantbruksuniversitet
- The Swedish University of Agricultural Sciences
- Umeå universitet
- 12 more »
- « less
-
Field
-
complex contexts through statistical models, machine learning (ML) methods, and artificial intelligence (AI). This includes working with performance, scalability, resilience regarding platform architectures
-
estimated from observed data. The overall aim of the project is to develop statistical theory, methodology, and computational methods for such complex data problems, with a particular focus on models
-
conducted in collaboration with BioMS and experts in proteomics and peptidomics at Lund University. The duties include: Planning and conducting experiments. Developing and optimizing methods for sample
-
of the project is to develop statistical theory, methodology, and computational methods for such complex data problems, with a particular focus on models for latent variables and their connections to modern
-
regions. Implementation methods will include: Seasonal sampling of food web components, from primary producers to fish, during open-water (summer) and under-ice (winter) conditions. Analysis of biomarkers
-
modelling of flow and transport, analysis of uncertainties in model predictions, and development of efficient methods for evaluating their implications for geological repository safety. The methods will be
-
the Nordic countries and North America. The project will use samples and data collected from Arctic/alpine lakes in Sweden and other circumpolar regions. Implementation methods will include: Seasonal sampling
-
biological data. Analyzing and visualizing collected data using appropriate statistical methods and relevant software. Conducting literature reviews and completing doctoral-level coursework. Presenting
-
Researcher in Fire safety engineering focusing on fire dynamics and material behaviour (PA2026/2714)
. The department conducts research and teaching linked to society's needs for infrastructure and construction. This also includes consideration of safety aspects and the development of methods for managing
-
of behavioral data, including the use of advanced statistical methods Experience with statistical analysis tools such as SPSS or equivalent Documented experience in scientific writing, for example in the form