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advanced statistical and epidemiological analyses. Complete PhD courses (approx. 30 ECTS credits). Analyze data from national health registers and surveys. Write and publish scientific articles in peer
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scientists and researchers across five Danish universities building training and research infrastructure. Your competencies We expect you to have a master’s degree in statistics, computer science, mathematics
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looking for applicants for a PhD scholarship within the field of health economic evaluation. We are looking for a person with a relevant degree (e.g. health economics, economics, statistics, data science
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competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT4 on Reliability and Trustworthiness
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for empirical statistical analysis, as well as possible experimental designs to validate findings. Empirical setting The research will utilize data from the Danish Innovation Fund, integrated with databases
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to the PhD project ie. processing and analysis of dietary intake data, statistical analyses (eg. linear mixed models) as well as evaluation of child growth and body composition data. Relevant publications
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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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are looking for a person with a relevant degree (e.g. health economics, economics, statistics, data science, public health science). Are you passionate about contributing to a groundbreaking interdisciplinary
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qualifications: Specialised understanding of product development and quality testing Experience with statistics, energy consumption analysis, and Life Cycle Assessment (LCA). An interest in working together
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career plans. This may include the development and implementation of tasks that probe human cognition and behaviour; statistical analysis and computational modelling of behavioural and neural data; and the