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dynamics simulations. You will contribute to the development of broadly applicable electronic structure methods, new software, and machine learning methods with the specific goal to accelerating
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questions in the field of mathematical automation in numerical analysis or approximation theory. o You implement the developed methods in Lean. o You become an active team member of the "Mathematical Data
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the design of nanostructured catalyst materials to provide optimal reaction selectivity and activity. You will contribute to the development of new dynamics software and machine learning methods
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. Visual Data Analysis you will develop methods/tools to enable more effective research, e.g., enabling medical professionals to explore and discover patterns in disease progression and to assess treatment
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"Urban Development & Mobility Transformation" focuses on researching and applying innovative tools and methods for sustainable urban development and the integrated planning of mobility systems. For our
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(quantitative research methods and advanced proficiency in statistical software such as Mplus, R, etc.) • Teaching experience/experience in e-learning • Experience in student supervision • Excellent
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students. You participate in evaluation measures and in quality assurance. You take on administrative tasks in research, teaching and administration. This is part of your personality: Completed doctoral/PhD
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University Assistant Praedoc to join the dynamic research team led by Univ. Prof. Sara Merino Aceituno, PhD. The research areas developed by the team are in particular related to kinetic theory applied
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rapidly urbanising tropical cities. The project will develop a hybrid modelling framework combining process-based and statistical methods to examine causal feedbacks among urban growth, social vulnerability
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are currently looking for PhD candidates for 5 different research topics. The position advertised here focuses on affordances of open science infrastructures. Data sharing is central to contemporary science. As