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experience in project design, analyses, interpretation and scientific publication and be involved in a project that develops future AI tools for genomic analysis. Examples of areas in which the scholarship
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analysis, Python programming, and deep learning frameworks (e.g., TensorFlow, PyTorch) is expected. Prior work in cancer research or medical imaging is an asset. The successful candidate will join an
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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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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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, proof assistants, term rewriting systems, optimizing compilers, program analysis tools, constraint solvers, or similar. Familiarity with linear algebra libraries and high-performance computing