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machine learning, deep learning, or AI. Solid mathematical, algorithmic, or physics background, distinct analytical skills. Very good programming (Python, C++) and computer (Linux, Windows) skills
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, computer science, or mathematics (or a related field), with a focus on robot vision and control, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills
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on computer vision, image processing, or machine learning Solid mathematical and physics background, distinct analytical skills Very good programming (Python, C++) and computer (Linux, Windows) skills
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isotherm parameters directly from molecular properties. These predictions will be integrated into the open-source CADET simulation framework, enabling fully predictive process simulations without extensive
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the DAAD in accordance with the Federal Data Protection Act and with the EU Data Protection Regulation insofar as this data is needed to process the application. Submitting an application General information
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regression models to isolate task-related submanifolds and their respective role for sensory processing and task performance Analysis of the data to identify higher-order spike correlations and their temporal
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submanifolds and their temporal dynamics during behavior Leverage dimensionality reduction and regression models to isolate task-related submanifolds and their respective role for sensory processing and task
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, extending them with physics-based approaches, and adapting existing physics-integrated neural network approaches for stress prediction in arterial walls and plaque. Another part of the project is exploring
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Association. At the Leibniz Institute on Aging – Fritz Lipmann Institute (FLI), we investigate the fundamental biological processes that drive aging. Our research combines molecular, cellular, and systems-level
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on the application procedure are available on the programme website . Application Deadline Up-to-date information is available on the programme website .