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polynomial processes, rough paths, signature methods, neural S(P)DEs, McKean-Vlaslov equations, stochastic portolio theory, control theory and contemporary stochastic volatility modeling. The successful
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education in chemistry; • advanced knowledge in environmental trace metal chemistry (including thermodynamic modelling); • specific knowledge on interactions between plants and trace metals (e.g
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you will be part of the research team of Univ.-Prof. Tarja Knuuttila. The main research areas associated with this professorship are general philosophy of science, with focus on scientific modeling
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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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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 influence: The Special Unit for Quality Assurance conducts evaluations of organisational units, study programmes, courses and researchers. It is responsible for quality checks in appointment and tenure track
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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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: 01.09.2025 (MM-DD-YYYY) | Working hours: 30.00 | Classification CBA: §48 VwGr. B1 Grundstufe (praedoc) Limited contract until: Job ID: 3933 The research team “Climate Dynamics and Modeling”, co-led by Prof
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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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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