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multi-parameter ion-beam tuning procedures (collaboration with Univ. of Vienna and HZDR) and developments of machine learning (ML)-algorithms for optimization of beam parameters and control of relevant
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stellar population models applied to state-of- the-art spectroscopy requires novel optimisation algorithms and efficient programming. • You can show a proven track record in object-oriented programming as
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, algorithm implementation, programming from a variety of biotechnology platforms, and oversee quality check. Design and prepare materials and courses for training on various bioinformatics software and
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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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. Applicants should have strong expertise in computational analysis of electrophysiological data as well as proficiency in large language models and machine learning algorithms. First-hand experience in
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control, state estimation, and path planning algorithms for single and multi-agent robotic systems (UAVs). develop and train AI models for practical applications such as real-time object detection and
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in 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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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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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