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be able to demonstrate proficiency in statistical analyses and have a high proficiency in spoken and written English that includes very good scientific writing skills. As postdoctoral appointments
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transparent models. The Privacy-aware transparency decisions research group (led by Prof. Vicenç Torra) conducts research in data privacy for data to be used for machine and statistical learning. It is well
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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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, genotyping, immunohistochemistry, RNA in situ hybridization and statistical analyses. Qualifications The ideal candidate should have a PhD in molecular or developmental biology, neurosciences, photoreceptor
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intelligence. The candidate should be experienced with qualitative research methods, including surveys and questionnaires, interviews, focus groups or statistical surveys. Familiarity with the relevant European
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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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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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the position Experience with independent planning, execution and evaluation of experiments, including statistical analysis Familiarity with theory and techniques of chemical analyses or metabolomics is required
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statistics. Required qualifications and skills: Solid understanding of maritime transport systems and risk assessment. Proven programming skills (to be demonstrated prior to starting the position). Excellent
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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