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. The team uses innovative large datasets and applies rigorous empirical methods to estimate causal effects. The successful candidate(s) will be part of the PhD programme of the Department of Management
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Pomeranz from the University of Zurich, as well as the postdocs, PhD students and other student research assistants involved in the project. You will be responsible for coding the content of Swiss collective
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extremes under different air pollution along a climatic gradient in Europe. Moreover, we will use statistical (e.g., random forest, generalised additive models) and process-based (e.g., SPA) models
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the statistical software package Stata and/or R (Python is a plus) Prior experience with data cleaning and management Fluency in German and English Excellent writing skills (in German and English) Very good
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and statistical methods to detect and characterize trait-associated sequence variation from short and long-read sequencing data. We are looking for a motivated researcher who is eager to work on cutting
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experience in Machine Learning with a PhD degree from a university in Computer Science, or related fields, with a proven track record in statistical machine learning, deep learning, and graphical modelling