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well as specifics of walking quality? The general concept is to generate machine learning as well as statistics-based models to extract movement patterns from movement/locomotion/walking/gait dataset collected via
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performance and availability of funding. The starting date is as soon as possible but can be negotiated. Profile You must have a PhD in physics, climate sciences, statistics or a related subject, ideally
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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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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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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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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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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