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Field
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. Your tasks identify relevant satellite datasets of irrigated areas, as well as of hydrometeorological, land surface and vegetation variables apply modern statistical methods on these datasets to detect
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(e.g., Public Health, Medicine, Global Health, Respiratory Medicine). Strong background in epidemiology, clinical research, or biomedical sciences. Proficiency with data analysis and statistical software
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. Applications by email will not be considered. Application procedure and conditions We kindly request applicants to provide their nationality for statistical purposes only, as part of our commitment to promoting
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methodologies, including open-ended interview research quantitative analysis, survey design, statistical analysis. How to apply Apply for this scholarship at the same time you apply for admission to a QUT Doctor
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Action Plan for a national noise hot-spot. Ideal profile: honours degree (2.1 +/MSc) in environmental science, data science, public health, geography or similar; experience with R/Python statistics
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methods Descriptive statistics and logistic regression. Impact This project will inform the implementation of interventions aimed at increasing self-testing rates. 2) Missing annual flu vaccination Data
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interfaces and driver modelling Implementation of control algorithms in mechatronic systems Experimental design and statistical methods Vehicle testing and test methods involving human test subjects What you
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extraction techniques. Strong knowledge of protein science and its application in food systems. Proficiency in analytical techniques relevant to food and protein characterization. Skills in statistical
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at the Faculty of Mathematics at TUD. Tasks: generation of hyper uniform patterns (point, scalar and vector fields) application of topological data analysis tools such as persistent homology and graph statistics
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 3 months ago
an international team of researchers applying advanced quantitative methods and statistical modelling to a cutting-edge population topic. Students with an excellent master’s degree (distinction