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Field
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for livestock systems in East Africa, and in the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We
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engineering methods (e.g., via CRISPR). Plan and execute experiments to probe robustness of tissue morphogenesis, particularly through quantitative imaging and large-scale molecular profiling (e.g., via scRNA
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to state-of-the-art applications in geophysics executed on supercomputers, as well as the presentation of the results to the scientific community in journals, at conferences, and as lecture contributions
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scientific career. About us TUM’s new Computational Pathology and Medical Machine Learning lab (*2021) develops methods of machine learning (ML) and artificial intelligence (AI) for the analysis of digital
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at the newly founded Global Center for Family Enterprise (Prof. Dr. Miriam Bird). Expected starting date is April 2023 or by mutual agreement. The scientific employee (postdoc) will be employed on a 100
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available in the further tabs (e.g. “Application requirements”). Programme Description The programme is intended for outstanding junior post-doctoral scientists from Germany, Austria and Switzerland from all
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technologies to fundamental physics questions. The advertised positions will be part of the project “QS-Gauge: quantum simulation of lattice gauge theories”, funded by the Emmy Noether programme of the DFG
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FIZ Karlsruhe – Leibniz Institute for Information Infrastructure is one of the leading provider of scientific information and services and a member of the Leibniz Association . Our core tasks are
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wellbeing. They will use modeling approaches to combine natural and social science data. You will focus on developing and implementing mixed modeling approaches to test pathways through which structure
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the subtropics in Latin-America. The research programme will examine productivity of grasslands, nutrient stocks and cycling and their relationship to biodiversity. We conduct experiments in the field