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-disciplinary and cross-cultural cooperation. The research revolves around four topic areas: Business models, decision processes and economic analyses Holistic interdisciplinary methods for modelling, analysis
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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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Engineering. Familiarity with partial differential equations (PDEs) numerical analysis and / or data science and statistics will be an advantage. Number of scholarships: One Contact person: Associate Professor
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Stochastics and mathematical finance Discrete mathematics and optimisation Discrete geometry Numerical mathematics Applied analysis Mathematics for AI Course organisation The BMS programme is divided into two
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experience with: Signal processing Experimental design and data analysis Furthermore, the successful candidate is expected to: Have excellent knowledge of English (written and spoken). Have high self
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Neuroscience uses theoretical approaches from this broad range of disciplines to integrate experiment, data analysis and modelling in order to understand the brain. Furthermore, it makes a scientific language
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | 3 days ago
this, IMPRS CoNI offers high performance computing facilities for computational modelling and data analysis. The modules covered ensure a structured and comprehensive approach and provide the important basic
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-waiting – were successful spies in seventeenth-century England. This is what Nadine Akkerman describes in her book Invisible Agents, the first analysis of the role of female spies in the seventeenth century
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events with the GOTO telescope network. Projects focussing on thermonuclear bursts will involve analysis of new and archival data from satellite-based X-ray telescopes, and running numerical models
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of employment). The successful candidate should possess evidenced (e.g. by relevant PhD thesis and publications) knowledge of stochastic and rough analysis. Knowledge of rough path signatures, numerical methods