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with high-dimensional, often noisy, data sets; and mathematical modelling approaches that reduce the dimensionality of parameter spaces and produce mechanistically realistic, experimentally testable
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in their careers and professional development. The Entrepreneurs Campus at Ulm University offers opportunities for creative academics who want to develop their ideas into products or business models
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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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Degree Doctor of Philosophy (PhD), Division of Mathematics and Natural Sciences or Doctor rerum naturalium (Dr rer nat) Course location Göttingen In cooperation with Max Planck Institute for Solar
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Max Planck Institute for Human Cognitive and Brain Sciences • | Leipzig, Sachsen | Germany | about 8 hours 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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Max Planck Institute of Molecular Plant Physiology • | Potsdam, Brandenburg | Germany | about 8 hours ago
approach combining molecular biology, genetics, genomics, epigenomics, metabolomics, biochemistry, biophysics and microscopy with bioinformatics and modelling. We work with Arabidopsis thaliana, tobacco
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, Mathematical modelling, Biology, Environmental Science, Physical Geography, or related fields. • Specific research in agricultural-environmental disciplines, and particularly with respect to livestock
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analysis (TEA) or an affinity towards these research questions. - Basic knowledge in bioprocess design, bioengineering and/or mathematic modeling - Affinity towards research question in life cycle
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messengers transported by the flow or even the pressure of the fluid itself. In an interdisciplinary team, you will either develop theoretical models of the feedback between flow and network architecture
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the 01.10.2022. Your Responsibilities: You will work at the cutting edge of privacy-preserving deep learning research with a focus on one or more of the following topics: - Optimal model design for differentially