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sites will not be located directly at the source of emissions, which will require transport infrastructure. As part of this work, you will model spatially resolved transformation paths for the energy
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innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry tools
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with you on board! We are seeking a highly motivated PhD student to join our research team studying the role of NMDA receptors in psychosis, using translational mouse models of anti-NMDA receptor
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: Develop innovative machine learning architectures for the mining, prediction, and design of enzymes. Combine state-of-the-art ML (e.g., deep learning, generative models) with computational biochemistry
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Universität Berlin. The position is part of the research group Quality.2 (Phytonutrient Management) in the programme area ‘Plant Quality and Food Security’ (QUALITY). The aim of the research project ‘GluAmin
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. Santiago Botía with close collaboration with Dr. Christoph Gerbig of the Atmosphere-biosphere Signal Attribution (BSAT) and Atmospheric measurements and mesoscale modeling (ATM) groups at the Max-Planck
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computer vision in dusty conditions by incorporating hyperspectral cameras. In addition, assisting in project applications and general development duties of the Chair. The position is available from
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Kolter, Tjibbe Donker and Philipp Henneke analysis of multiscale single cell ‘omics data in in experimental and human models reference genome and transcriptome assembly and annotation across species
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designs in terms of their techno-economic characteristics an optimization model is to be developed in the institutes’ inhouse modelling framework FINE (https://github.com/FZJ-IEK3-VSA/FINE) in
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, master’s degree) in transportation, computer science or related fields experience with transport models and/or simulation tools interest in interdisciplinary research on the analysis and modeling