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. Your work tasks This Postdoc sits at the intersection of mathematics, statistics, data science, and public health. The goal is to develop new methods that allow researchers to learn from sensitive health
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/or eating disorders, data analysis and statistical modeling. Prior experience working with Danish registers is an advantage. As a person, the ideal candidate will have good interpersonal skills, will
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analyze interviews with company representatives, trade unions, labour inspectors and other authorities, and experts. Gather and analyze supplementary data such as statistics, archival data, media sources
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The SDU Adaptive Intelligence Lab (ADIN Lab) (https://adinlab.github.io/ ) located under the Data Science and Statistics Section of the Department of Mathematics and Computer Science (IMADA
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data. Statistical analysis using R and/or Python. Reproducible computational workflows. Scientific writing and publication. Microbiome research and host-associated microbial communities. The ideal
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methods and their underlying assumptions and limitations. Demonstrated experience with statistical analysis of genomic and ecological data, including multivariate analyses, demographic inference, population
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statistics, AI and machine learning methods, including demonstrated experience in analysing multiple global change drivers, e.g. land use intensity, climate change, nitrogen deposition. Proven capability
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The Section of Biostatistics is looking for a postdoc to develop statistical methods for inference on causal effects in studies affected by non-random participation, particularly self-selection in
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materials. Use molecular dynamics, lattice-dynamical methods and statistical sampling to investigate local disorder, phase stability, temperature-dependent behaviour and structure-property relations
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-Norm) is preferred. Experience with citizen science, co-creation, or other participatory/qualitative research methods is an advantage. Strong quantitative and statistical analysis skills (e.g. SPSS, R