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Quantum Mathematics with emphasis on pure mathematics with relations to quantum theory or with emphasis on Quantum algorithms, Quantum software and Quantum computing. The targeted starting date
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both fundamental and applied research, from the development of algorithms, tools, and frameworks that advance scientific discovery to methodologies that utilize computational approaches to generate
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algorithms formulating industrial problems to make them accessible to quantum algorithms mapping quantum algorithms to specific use cases and applications optimizing algorithms in the context of such use cases
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the future of pediatric oncology, neurodegenerative disorders, and sickle cell disease. Job Responsibilities: Analyze biomedical data with minimal supervision by performing advanced analysis, algorithm
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, including image acquisition, processing, analysis, and interpretation Develop and validate new imaging techniques, algorithms, or software to improve diagnostic accuracy and patient outcomes Collaborate with
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. The most recent methodological research of the group includes algorithms for cell type deconvolution, high-resolution purification, and integration of single cell multi-omics data. This postdoctoral fellow
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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 to understand
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on stochastic Riemannian optimization algorithms, these methods still suffer from limitations in computational complexity. The post-doctoral fellow will build upon this preliminary work to investigate
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algorithms for dynamic structured data, with a particular focus on time sequences of graphs, graph signals, and time sequences on groups and manifolds. Special emphasis will be placed on non-parametric
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advanced AI algorithms to optimize and understand the optical properties of light-trapping surfaces. (more information can be found in the following News post ). You will work closely with colleagues both