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Field
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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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to fight blood cancer, optics, or lightweight components. In particular, tabular and image data are recorded during production. In the context of the thesis, DL - as well as ML pipelines are to be created
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to accomplish something new—complemented by teamwork and fostering personal relationships. From assistants, students, researchers, postdocs to professors; we are all working hand in hand, are highly committed
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on ranges from concept and prototype development for industrial laser manufacturers to publicly funded projects in the field of basic research, for example in the generation of EUV radiation through non
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project in Germany as part of your fellowship; if you are a postdoc, long-term academic research (12-24 months). It should focus on combating climate change, adaptation strategies, preserving ecosystems and
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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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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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to accomplish something new—complemented by teamwork and fostering personal relationships. From assistants, students, researchers, and postdocs to professors; we are all working hand in hand, and are highly
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for their relevance in alpha- and flavivirus replication. Methods include but are not limited to: molecular cloning, cell culture, qRT PCR assays, co-IP-WB, imaging and RNAi experiments. We expect at least 10 months of
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zusammen mit insgesamt elf Postdoc WissenschaftlerInnen aktiv am wissenschaftlich-akademischen Diskurs zur aktuellen Forschungs- und Entwicklungsfragen im Bereich des Grünen Wasserstoffs teilnehmen. Von