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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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learn new advanced analysis techniques (e.g., in Matlab, R, or Python) if relevant for the task. Write up research results in the form of journal articles. Participate in and co-arrange national and
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information Further information may be obtained from Professor David R. Fuhrman (drfu@dtu.dk ). You can read more about DTU Construct at www.construct.dtu.dk . If you are applying from abroad, you may find
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in the Hempel Foundation Coatings Science and Technology Research Center (CoaST), spanning the entire value chain of industrial coatings R&D. To virtually visit the state-of-the-art labs
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software (primarily SAS, SQL, R, Python, and Stata) Experience of working with Danish registry data primarily via Statistics Denmark’s project database and researcher scheme Knowledge of and practical
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Postdoc in assessing carbon sequestration potential of different wetlands as nature-based solutio...
qualifications: A solid background in programming using Python, R, or other languages. Teaching and supervision experience at the BSc and MSc level. Interest and experience in developing competitive national and
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qualifications: A solid background in programming using Python, R, or other languages. Teaching and supervision experience at the BSc and MSc level. Interest and experience in developing competitive national and
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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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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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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