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optimization – with rigorous theoretical analysis. The ideal candidate has strong machine learning and AI expertise and is comfortable with – or eager to learn – large-scale multi-GPU experimentation
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of molecular and biological matter using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts
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Disse), the Chair of Geoinformatics (Prof. Thomas H. Kolbe), and the Chair of Algorithmic Machine Learning & Explainable AI (Prof. Stefan Bauer). The project aims to develop an integrated urban flood
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, Data Science, Machine Learning, or a related field. Experience and skills · Strong knowledge of AI, Machine Learning, data-science (e.g., neural networks, deep learning, autoencoders, GANs, active
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sequencing and researching disease in patient cohorts, working with machine learning techniques and programming computers. The candidate will learn about different flavors of metagenomic sequencing, how