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in machine learning Extensive experience with either computer vision or image analysis Good knowledge of deep learning packages, PyTorch Familiar with foundation models (vision large models or multi
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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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and population genetic research Deep understanding of Evolutionary Biology Experience or interest in learning lab work (e.g. DNA extractions and library preparations) Research experience with genomic
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installations such as a deep geological repository for nuclear waste is both a strategic necessity and a challenge. The Department of Actinide Thermodynamics of the Institute of Resource Ecology is looking for a
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Your Job: In this position, you will be an active part of our Simulation and Data Lab for Applied Machine Learning. Within national and European projects, you will drive the development of cutting
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2019, unites top PhD students in all areas of data-driven research and technology, including scalable storage, stream processing, data cleaning, machine learning and deep learning, text processing, data
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models. Your tasks: Research, development, and evaluation of Machine Learning and Deep Learning methods Prototype development Literature review Publication and presentation of scientific results in
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the 01.10.2022. Your Responsibilities: You will work at the cutting edge of privacy-preserving deep learning research with a focus on one or more of the following topics: - Optimal model design for differentially
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of the GPN: Cluster 1: Partnership in development cooperation: access, accountability, and deep participation Cluster 2: Partnership in the global economy: agriculture, finance, and energy Cluster 3