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-based and aircraft experiments with innovative modelling to study the fundamental physical and chemical properties of aerosol particles and clouds. Current research focuses on related but different areas
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-sophisticated laboratory, ground-based and aircraft experiments with innovative modelling to study the fundamental physical and chemical properties of aerosol particles and clouds. Current research focuses
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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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% of their graduating classes) have a strong quantitative background have an interest in acquiring methodological skills in areas such as formal (mathematical) modelling and/or (quantitative) empirical testing
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promise in any area of theoretical solid-state physics, including but not limited to modeling of oxides and their surfaces, machine learning methods, and/or development of novel solutions to solve the many
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interviews between selected applicants and faculty members (match-making step) invitation of selected applicants for (online) panel interviews All applications must be handed in online through the University
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. This project will critically examine this landscape, exploring what kinds of data sharing and re-use practices are afforded by different models for open science. It will lay the groundwork for novel approaches
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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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to be coupled to model-free analysis of molecular dynamics simulations. This includes work in the biochemical wet-lab as well as with prototype NMR spectroscopy and computational tasks. You have previous
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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