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comparative embedded ethics approach, examining neuroAI development in both clinical neuroscience and neurorobotics settings. Your tasks: The postdoctoral researcher will play a central role in the project and
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, and unmodeled dynamics remains a key challenge. This position focuses on developing and validating methods that jointly address safety, performance, and reliability of learning-based control and
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(e.g. RNAi, CRISPR/Cas9, small-molecules). In this context, we also develop new computational tools for automated analysis and data visualization. These include algorithms and software applications
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(ECLECTX team). This person occupying this position is planned to work on modeling computing elements, established and emerging, at different levels of abstraction, design and development simulation tools
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning
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use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a
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complex multiphysics problems. The coupling is done across package boundaries. This also requires more sophisticated approaches in load-balancing. Finally, the newly developed algorithms will be tested and
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. TASKS: Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on L1-norm minimization and compressed sensing
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project, we are looking for a strong candidate to contribute to the development of quantum algorithms and applications, focusing on quantum walks and quantum machine learning on graph structures. Your