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Job Description The section for statistics and data analysis is looking for a Postdoc to join the section, with the aim of strengthening the section’s work within scientific consultancy in
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Research & Innovation Centre (BRIC), working at the intersection of genomics, molecular biology, and artificial intelligence. The lab performs statistical analysis of large-scale datasets (cancer genomics
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Science including quantitative and qualitative consumer research methodologies, and experience in designing consumer studies in and out-side Denmark. Solid experience in statistical analysis are preferred
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Three-Year Postdoc Opportunity in Ecosystem Structure, Functions and Services in Offshore Marine ...
of flora and fauna, stable isotopes, programming in R, statistical analysis, and GIS, will be beneficial. Our Department: The Department of Biology at SDU is a dynamic and multidisciplinary environment
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Research & Innovation Centre (BRIC), working at the intersection of genomics, molecular biology, and artificial intelligence. The lab performs statistical analysis of large-scale datasets (cancer genomics
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and statistical tools to identify patterns in large datasets The candidates should demonstrate evidence of self-driven and independent research capability, excellent collaboration and communication
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within DanSIC and CIMP. Collaborate with internal and external researchers to design experiments and analyze complex datasets. Perform statistical analyses and data visualization to interpret and publish
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(programming, digital signal processing, modelling, statistics) is sought. The project involves collaboration with Prof. Marco Steinhauser (University of Eichstätt-Ingolstadt, Germany) and Dr. Ramakrishna
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(programming, digital signal processing, statistics) is sought. Qualifications Ideally, applicants for the position should satisfy the following requirements: PhD degree in psychology, cognitive (neuro)science
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CFD workflows and Lagrangian particle/cell tracking to extracting actionable insights with statistical learning and AI/ML—ultimately enabling more robust scale‑up, smarter process control, and faster