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Degree PhD (Division of Mathematics and Natural Sciences) or, alternatively, Dr rer nat Course location Göttingen In cooperation with Max Planck Institute for Multidisciplinary Sciences (MPI-NAT
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, medical informatics, databases, data mining, machine learning, applied mathematics, biomedical modelling and analysis of complex networks. Joint data science projects between the different partners
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into the following sections: A - Algebra, Number Theory and Logic B - Analysis and Differential Equations C - Discrete Mathematics D - Geometry and Topology E - Numerical Mathematics and Scientific Computing F
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its rich information content, conventional analysis methods have not yet fully realized its potential. This research project aims to develop a robust AI foundation model based on modern Transformer
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of systemic neurosciences: single cells to complex systems system analysis to mathematical modelling perception and cognition to mind and neurophilosophy biology to technical solutions Additional support is
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coverage of both theory and empirical analysis, the PhD programme at GSEFM offers a two-year cycle of doctoral-level courses developed specifically to transmit a rigorous methodological framework in the core
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dedicated to world-class teaching and research in medicine and STEM . Its 10,000 students are distributed among the faculties of medicine, engineering, computer science and psychology, mathematics and
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of the University of Bremen: Production Engineering, Business Studies / Economics, Mathematics / Computer Science, Physics / Electrical Engineering, and Law. Associated partners are the BIBA – Bremer Institut für
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German Institute for Economic Research (DIW Berlin) • | Berlin, Berlin | Germany | about 20 hours ago
-level mathematics, microeconomics, macroeconomics, economic policy, and advanced econometrics. In the summer semester (April to July), doctoral students choose either microeconometrics or time series
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Group (EASE IRTG), Empowering Digital Media (EDM), the Research Training Group HEARAZ , the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms