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Mathematics/ Approximation Theory to be filled by the earliest possible starting date. The Chair of Applied Mathematics, headed by Prof. Marcel Oliver, is part of the Mathematical Institute for Machine Learning
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machine learning approaches. These are similar to earlier work on charge and excitation energy transfer (see https://constructor.university/comp_phys). The project for the PhD fellowship is slightly more
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 25 days ago
not strictly required. Skills or interest in MRI processing (especially diffusion MRI), biophysical neural modeling, and machine learning are welcome. What we offer The Institute offers a world-leading
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the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission analysis, and infrared thermography
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-weighted and functional MRI, intracranial EEG) Multi-scale modelling of human brain development Using machine learning frameworks to interrogate the relationship between brain development and cognitive
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synthesis over all relevant length scales (e.g. cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) • High resolution analysis, monitoring of chemistry
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performance in fuel cell (biogas) and co-electrolysis applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under
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applications. To achieve this, you will employ computational fluid dynamics (CFD) and machine learning (ML) to investigate degradation mechanisms under various operating conditions and develop strategies
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at demonstrating how teacher learning can be made robust in an event-based framework, that is, when both the teacher model and the learning rules are event- based. The combination of excitable teacher dynamics and
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty