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learning and 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
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of the PhD topic (subproject A7- Reinforcement learning for mode choice decisions): This PhD project will develop and implement a Deep Reinforcement Learning (DRL) model for dynamic mode choice within
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, geometallurgy or related field Experience in either stochastics, deep learning or minerals processing is needed Structured and solution-oriented working style, analytical thinking and above-average committment
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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
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collaboration with Q.ANT GmbH in Stuttgart, a deep-tech company that develops photonic computing and photonic sensing products. The goal of this project is the development of highly integrated vapor cells with
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: Develop innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry