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Postdoctoral researcher in marine ecosystems modelling for the Marine and Continental Waters Program
Research FieldOtherEducation LevelPhD or equivalent Skills/Qualifications Required qualifications and experience Ph.D. in Marine Sciences, Marine Ecology, Statistics, Biology, or related fields applied
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in Translational Medicine Knowledge of statistics and experience with software such as GraphPad, R Experience and knowledge: Required: Minimum of 3 years of experience in metabolism research Prior
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knowledge in statistical physics, biophysics, excellent programming skills (C++, Python,...), proficiency in spoken and written English Specific Requirements Experience with scientific modelling Experience
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of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep learning and the use of robust statistics. This work is naturally extended to studying
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of inflation and phase transitions in the early universe. We are developing new data analysis methods like the use of deep learning and the use of robust statistics. This work is naturally extended to studying
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of statistical packages (Stata, R or equivalent). • Experience in spatial analysis and use of Geographic Information Systems (GIS). • Ability to work with large databases and data management tools. Languages
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epidemiology and managing large databases and statistical analysis with R, Python or similar. Project management (drafting, application, execution). Fluency in English. Specific Requirements Mobility and
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and statistics You are experienced with flow cytometry and/or single cell genomics protocols Education and training A PhD in a relevant field (computational biology, genomics, stem cell biology
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research paper as first or co-first author You have some experience in experimental work Desirable but not required/ Nice to have A strong foundation in machine learning and statistics You are experienced
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reviews, manage data collection and analysis, and perform statistical evaluations to support robust scientific conclusions. Provide scientific input and expertise for ongoing and future research projects