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The research group Genetics and Physiology of Root Development studies crop root anatomical and architectural traits. Research is mainly focused on cereals including barley, wheat, and maize. We
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candidates seeking part-time employment. Please indicate your request in your application. Position#6: TRR404-TUD-B07 Project: B07 Reconfigurable Architecture Project Leader
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, unsupervised and reinforcement learning that can be combined with, enhance or replace methods from computational engineering and computer simulation explore and evaluate usability of system architectures such as
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The research group Genetics and Physiology of Root Development studies crop root anatomical and architectural traits. Research is mainly focused on cereals including barley, wheat, and maize. We
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architectures, capable of capturing the structure of complex, high-resolution NMR spectra – analogous to how language models such as ChatGPT learn the structure of human language. One of the primary goals is to
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architectures and principles from Bayesian neural networks and biological sequence models, including large DNA and protein language models. The project also aims to develop a prototype federated learning
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The research group Genetics and Physiology of Root Development studies crop root anatomical and architectural traits. Research is mainly focused on cereals including barley, wheat, and maize. We
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Leibniz Institute of Ecological Urban and Regional Development (IOER) • | Dresden, Sachsen | Germany | about 16 hours ago
. Approximately 18% of its students come from abroad. Location Dresden, the capital of Saxony and home to more than 550,000 inhabitants, is located on the Elbe River and is renowned for its baroque architecture
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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
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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