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The Leibniz Institute for Prevention Research and Epidemiology – BIPS in Bremen, Germany, invites applications for a three-year PhD program in epidemiology, statistics, and prevention and
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foundations of ML · Explainability, trustworthiness, and robustness of ML · Deep learning architectures and Generative AI · Big data and cloud-based systems · Human-centered data analytics and data
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or art space, relating to themes such as Archaeology, Architecture, Art, Cultural History, Natural Sciences and Technology and a relation to the overarching theme of the programme next year. Commitment
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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 tools
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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
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-level modeling, or computer architectures or even quantum computers can be helpful but is not necessary Enthusiasm for unconventional, interesting interdisciplinary work - especially at the intersection
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available in the further tabs (e.g. “Application requirements”). Objective The aim of this programme is to promote artistic cooperations with German host institutions. The scholarships are funded by
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with a master's or diploma degree Fundamental understanding of mixed-signal circuit architecture (e.g., ADCs, DACs) Experience in deep learning, hardware development, or memory technology is a plus
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their system-level integration Develop design architecture and break down requirements into functional blocks Create and execute test benches for RTL and timing simulations Perform formal verification
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research focuses on the study of quantum magnetism at the atomic scale. We build artificial quantum architectures from single atoms and molecules on surfaces and on probe tips, control their spin states, and