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the integration of large-scale biological datasets derived from both the host and the microbiome, employing advanced statistical methods and cutting-edge artificial intelligence techniques to uncover novel insights
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and optimize large-scale training and inference runs for foundation models on JUPITER (multi-GPU/node, mixed precision, parallelization, I/O optimization) Integrate multimodal data sources (e.g., scRNA
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invasive sensing tools to monitor metabolites, oxygen, carbon dioxide, pH, and other parameters. Ideally, the methods can function in parallel and on a large scale. The research is vital to understand key
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multi-disciplinary approaches to answer these key questions including; immunology, oncology (in vitro model-organoid systems, ex vivo tissue culture), microbiology, next generation sequencing (16S seq
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of the AGNs). High motivation for working with simultaneous multi-frequency VLBI observations and achieving the full potential of VGOS observations is desired. Your responsibilities: Develop pipelines
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of Livestock Systems is newly established at TUM and will include several postdocs, PhD students, and technical staff. The team will work on various topics, including multi-scale analyses of productivity
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18.10.2022, Wissenschaftliches Personal The lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is looking for a Post-Doc. The task will be the multi-modal modeling of medical data
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at TUM and will include several postdocs, PhD students, and technical staff. The team will work on various topics, including multi-scale analyses of productivity, nutrient and water cycling in livestock
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electrochemical gas sensor (PEGS) based on fast Li-ion conductors. The fast ion-conduction characteristics of Li-based materials unlock the possibilities of cost-effective, low-power, multi-sensing arrays with a