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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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for the modeling and simulation of 3D reconfigurable architectures e.g. based on emerging technologies (e.g. RFETs, memristive devices), and the evaluation with e.g. machine learning and image processing benchmarks
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defects of smectic-liquid crystal order in developing cross-striated muscle, or use machine-learning to expand existing custom-built image analysis pipelines (Python, Matlab). To learn more about this
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challenging, and new theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers