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Experience with satellite remote sensing and geographic data Excellent English communication skills (spoken and written) Highly desirable skills: Experience in GIS, remote sensing, statistical analysis and
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computational and statistical methods, with demonstrated experience in reproducible and scalable bioinformatics environments. The applicant will work in close collaboration with other Engblom lab team members who
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. Project overview The project involves applying advanced statistical analysis, machine learning techniques, and modeling approaches such as agent-based modeling to analyze diverse climate and socioeconomic
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research projects, as evidenced by scientific publications in internationally peer-reviewed journals - Good knowledge in genomics, bioinformatics and experience in statistical analysis of large datasets
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research experience in phylogenomics. You should have a strong background in bioinformatics, statistical phylogenetics and comparative genomics. Previous experience of working with de novo assemblies and
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bioinformatics, physics, statistics, computer science, computational biology, or related fields. Experience programming in Python (or R) as well as bash/shell scripting. Experience with machine-learning and deep
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model design and analysis as well as statistical model parametrization and validation techniques. This Postdoc position is part of a five-year research program funded by the Wallenberg Foundation, aimed
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education to enable regions to expand quickly and sustainably. In fact, the future is made here. The Department of Mathematics and Mathematical Statistics seeks a postdoctoral researcher within geometric deep
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epidemiology at the Department of Public Health and Clinical Medicine at Umeå University. We are looking for someone with an interest in statistical methods who wants to be involved in developing our research
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at the Department of Public Health and Clinical Medicine at Umeå University. We are looking for someone with an interest in statistical methods who wants to be involved in developing our research environment