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to the department Ph.D. program and will work on the development and analysis of statistical methods for machine learning, particularly in the context of high-dimensional models and with a particular focus on methods
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solutions and data processing pipelines for computational modeling, including data analysis and preparation of results for publication. You sign a doctoral thesis agreement within 12-18 months and complete
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the complex drivers of landslide risk in rapidly urbanising tropical cities. The project will develop a hybrid modelling framework combining process-based and statistical methods to examine causal feedbacks
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interest in using computational methods such as cognitive and psychophysiological modeling, (Bayesian) statistics and optimal experimental design, and agent-based modeling to address problems in
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applied or computational PDEs, who apply their expertise to address contemporary societal challenges. Areas of application may include, but are not limited to, climate modeling, ecology and biodiversity
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relationship is automatically extended to 4 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration.) Our program is modelled after leading US business
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programme of high-quality empirical research commensurate with the level needed for a PhD qualification, which advances the field of Environmental Psychology • Publish (or submit for publication) at least
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administration and organisation. We are looking for a (Permanent) Senior Scientist position in Atmospheric Transport Modelling 53 Faculty of Earth Sciences, Geography and Astronomy Job vacancy starting: 06/01/2025
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an outstanding research profile in applied or computational PDEs, who apply their expertise to address contemporary societal challenges. Areas of application may include, but are not limited to, climate modeling
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) Solid knowledge and some experience in statistical modeling High interest in working in an interdisciplinary research field Experience in academic writing and with research methods First experiences in