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scientific hypotheses numerically further develop the theoretical framework of the project extend and develop methods to apply functional connectivity methods and causal frameworks to neuronal spiking data and
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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
(or surrogate models) are approximations of classical numerical solvers with a very low computational cost. They form the core of a digital twin. Using machine learning techniques to build these meta-models
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environment, with regular seminars, numerous national and international collaborations, and daily interactions between experimentalists and theorists. During drought, the water columns under tension within
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, Physics, Computational Science, or a closely related field. A strong background in numerical methods, scientific computing, computational physics, or quantum computing. Excellent programming skills in
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modeling Demonstrated experience with mathematical modelling, and an ability to learn new concepts and (computational) methods as needed A demonstrated ability to work with programming languages such as R
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results, numerical modelling, and analytical approaches to support the development of respective reliable and efficient design concepts. Led by Prof. Christoph Odenbreit, the ArcelorMittal Chair of Steel
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concrete. About us Digital Structures with Mineral Materials is a new professorship at the TU Munich, focusing on the de-velopment of structural engineering, design, analysis and modelling methods
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scientific knowledge, such as physical laws, differential equations, and domain-specific constraints, to model, simulate, and understand complex systems. The project will explore modern SciML methods
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capability. Comprehensive education: Enjoy numerous opportunities for scientific training, skills development and problem solving. Diverse research areas: Work on numerical models, analyzing large data sets
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-trivial software. Solid understanding of algorithms, numerical methods, scientific computing, or machine learning. Ability and motivation to write clean, maintainable and well-tested code. Strong interest