44 distributed-computing-"Multiple"-"Humboldt-Stiftung-Foundation" PhD positions at Technical University of Munich
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project funded within the DFG Priority Programme “Illuminating Gene Functions in the Human Gut Microbiome” (SPP 2474) and be involved in microbiology and molecular microbiology of the gut microbiota
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to the computational complexity of climate models, these will be replaced by physics-informed deep learning surrogates in the aforementioned model coupling. The project will initially focus on one main application
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privacy-preserved fashion. Research topics include, but not limited to, i) handling distributed DL models with data heterogeneity including non i.i.d, and domain shifts, ii) developing explainability and
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privacy-preserved fashion. Research topics include, but not limited to, i) handling distributed DL models with data heterogeneity including non i.i.d, and domain shifts, ii) developing explainability and
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Nemetschek Institute of Artificial Intelligence for the Built World and conducted in collaboration with a range of other TUM chairs from the Geodesy and Computer Sciences domains. Tasks Your duties will
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and distributed systems. Applicants need to have a strong background and interest in algorithms and/or combinatorics. You ideally should have an MSc degree in Computer science with a focus on algorithms
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and an extensive server infrastructure for research Excellent training and career support opportunities (courses, personal coaching, ...) Your qualifications Master’s degree in Computer
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infrastructure for research Excellent training and career support opportunities (courses, personal coaching, ...) Your qualifications Master’s degree in Computer Science or a similar field Good theoretical
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15.04.2025, Wissenschaftliches Personal The Lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is inviting applications for a fully funded PhD position in interpretable machine learning for dementia prediction. see here:...
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new standards in computational metabolomics – facilitating biomarker discovery, advancing personalized health monitoring, and improving clinical decision-making. The work will be carried out under close