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, access, metadata, DMPs etc) Advise researchers in R and Python for data analysis and modeling. Required Experience In developing R functions for reproducible statistical analysis Professional or academic
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Steven Ludeke to discuss their expected degree timeline. Highly proficient in at least one statistical programming language (e.g., R, Stata, SAS, Python). Candidates that can show an aptitude for learning
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has experience with programming, data analysis and visualisation using Matlab, R and/or Python. Research in a clinical setting means that flexibility with work scheduling is occasionally required (e.g
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Knowledge and competences regarding the Danish VetStat database Skills in working with R for data management and analysis of big data Experience in collaboration with the livestock industry Understanding
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models implementable on digital infrastructure (e.g. cloud computing). The work will involve active engagement with various consortium partners in a fast-paced R&D process, as well as encompass extensive
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Postdoc in Psychiatric Epidemiology: Linking Register and Trial Data to Study Postpartum Depressi...
registers. Familiarity with survey-based data collection and handling of longitudinal data. Skills in quantitative analysis using relevant statistical software (e.g., STATA, R, or SAS). Experience with
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or administrative registers. Familiarity with survey-based data collection and handling of longitudinal data. Skills in quantitative analysis using relevant statistical software (e.g., STATA, R, or SAS). Experience
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experience with statistical tools (e.g. in R, MatLab, or Python) are expected. The team at DTU Aqua is highly international and knowing the Danish language is not needed. You must be available for boat-based
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degree and sufficient work experience would also be considered. Proficiency in Python for data analysis. Experience interfacing databases and R scripting will be an advantage but not required. Familiarity
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/accessibility/expression testing, trajectory inference, etc. An understanding, experience and published outcomes from analysing and interpreting large datasets using statistical programming languages (e.g. R