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-performance technologies to investigate the complex interplay between the human organism and food ingredients. The research group Mechanoreceptors/ Section II at Leibniz-LSB@TUM is currently looking for a PhD
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highly motivated doctoral student to join an ambitious project aimed at building machine and deep learning models to study the genetics of human disease. Funded as part of the Helmholtz AI program, the
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29.04.2021, Wissenschaftliches Personal This PhD position is in the field of resource management for wireless network that leverage “digital twins” modeling aspects of the physical (such as user
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, Google.org, SAP, Merck, TUM Klinikum, Holtzbrinck). Diverse research topics and technologies, including: Conversational Semantic Search, Question Answering Systems, Complex Information Extraction. Fact
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the aim of taking the complex spatial structure of clouds into account in climate models and global remote sensing. The position thus offers highly relevant and interesting opportunities for work and
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The Network Analysis and Modelling uses machine learning to investigate how genetic variation shapes gene regulation, protein function, and, ultimately, observable plant traits. We are seeking a
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to remote sensing and simu-lation modeling. A particular focus of our work is on mountain forest ecosystems. A quantitative understanding of ecosystem dynamics provides the foundation for the development
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’ is therefore to investigate the influence of glucosinolate-based amines on the formation of Maillard-like products in model systems and foods, to isolate and identify the resulting products and to find
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testing (e.g. cell culture and organoid models). As part of a third-party grant from the Federal Ministry of Education and Research, the BfR is working in collaboration with the University of Veterinary
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responsibilities: To carry out and complete your own research towards a doctoral degree. Design, run, and analyse equilibrium simulations with a coupled Earth-system model of intermediate complexity to investigate