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–2 years, total 3–4 years) on deep learning for medical imaging. This DFG-funded project focuses on developing deep learning methods for medical and scientific imaging. The Professorship for Machine
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03.06.2021, Academic staff The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and privacy-preserved
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03.06.2021, Academic staff The Albarqouni lab develops innovative deep Federated Learning (FL) algorithms that can distill and share the knowledge among AI agents in a robust and privacy-preserved
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host chromatin pathways (DFG Research Unit DEEP-DV, FOR5200). The group uses experimental infection systems, an array of high-throughput sequencing methods, and single-molecule live-cell imaging
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? No Offer Description About cellumation cellumation is a Bremen-based deep-tech company and spin-off from the Bremen Institute of Production and Logistics (BIBA). We develop the celluveyor – a modular
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Water Fluxes. Your tasks Build hybrid models, process-based and deep learning models, to capture ecosystem flux dynamics across space and time Develop generalizable models robust to climate variability
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informatics, or a related field - Strong programming skills in Python and experience with deep learning frameworks (PyTorch preferred) - Experience or strong interest in large language models, multimodal
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of artificial intelligence, machine learning and/or deep learning experience in scientific publishing and presenting research results knowledge or experience in public health research Personal skills Independence
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 22 days ago
learning/deep learning frameworks (e.g. PyTorch); experience in single-cell analysis or machine learning is advantageous. If you fulfill all the requirements, you may be eligible for a salary grade of up
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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