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combining imaging techniques and data analysis to provide a more integrated picture of life processes in the context of health and disease. To be a postdoc fellow at the AMBER programme you will get
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dynamical systems theory, including differential equations, simulation techniques, state-space and input-output representations, time-delay embedding, and/or time series analysis from experimental data
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the following fields: mathematics, physics, computational science, or engineering, and have a strong background in numerical analysis and scientific computing. Required qualifications include basic knowledge
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programming skills and finite element (FE) analysis experience is a requirement. Knowledge of machine learning, Matlab and Abaqus is also highly desired. Previous experience with parametrization and automation
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workshops, collection and analysis of data, writing of scientific texts, participation in and leading funding applications and other tasks related to RoC's activities e.g. within the framework of CoP and the
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, proof assistants, term rewriting systems, optimizing compilers, program analysis tools, constraint solvers, or similar. Familiarity with linear algebra libraries and high-performance computing