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directions are possible and encouraged. Collaborations include the National Weather Service MeteoSwiss, the Swiss Data Science Center SDSC, Prof. Nicolai Meinshausen (statistics and machine learning), various
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backgrounds include statistics, data analytics, and computer science, but students with other backgrounds are also encouraged to apply. Languages: English Workplace Workplace We offer ETH Zurich is a family
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statistics of our university Contact details of 2 referees Please note that we exclusively accept applications submitted through our online application portal before 30 June 2024. We will not consider
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your online application with the following documents: Curriculum Vitae, max. 2 pages Motivational Letter, max. 2 pages Transcript of records Grade statistics of the university Contact details of 2
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, teamwork and organizational skills Demonstrated experience in the modelling and analysis of omics data Solid understanding of biological/statistical data analysis methods Proficient programming skills (e.g
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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 data, and analysing it descriptively using the statistical software packages R or Stata Contributing to a research article documenting the dataset and the changes in the collective bargaining landscape
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analyze the data. Your task will be to correlate biomarkers derived from rTMS and NIRI with clinical outcomes, in order to personalize stroke rehabilitation and improve the recovery process. Statistical
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), material flow analysis (MFA), and statistical analysis. In particular, the following tasks will be performed in collaboration with the two doctoral students: modeling of the embodied and operational energy
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machine learning, seismic monitoring/imaging, statistical seismology, and geomechanical modelling. Project team members include Dr. Federica Lanza (ETH Zürich), Dr. Luigi Passarelli (INGV), and Dr. Antonio