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Field
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mimicked with in vivo models of metastasis, which provides unique opportunities to mechanistically dissect what drives the different cell states. You will link clinically relevant phenotypes to putative
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to the conserved neural organization of the mammalian brain, which provides a common computational blueprint across species despite profound differences in body plan and ecological niche. Motivated by this analogy
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in Python and R for data analysis, modeling, and visualization. Proficiency in building efficient pipelines that use optimized software to process large datasets. Proficiency in supervised
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research disciplines. For further information about the different research disciplines see https://www.ntnu.edu/imf/research . Are you motivated to take a step towards a doctorate and open exciting career
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- and micro-flow LC-HR-MS/MS for comprehensive multi-omics analysis. Proficiency in Python and R (essential) for data analysis, modeling, and visualization. Ability to work effectively within diverse
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for the position. Preferred selection criteria Solid theoretical background in robot perception and navigation. Deep foundation in modern machine learning. Solid programming skills in C++ and Python. Experience with
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Amsterdam by installing green roofs on existing buildings?' are important in fields such as urban planning, sustainability, and public health. It requires the transformation of maps combining different
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materials is deemed advantageous. Experience with numerical simulations (e.g., Finite Element, Finite volume, and other techniques) and programming (e.g., Python and MATLAB) is deemed advantageous. Experience
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Earth system models on different temporal and spatial scales to answer key questions of global change. Doctoral candidates of the IMPRS-ESM contribute to the development and application of Earth system
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domain shift, e.g. multi-modal data acquired by different scanners and imaging protocols. Publish and present scientific results at international conferences and high-impact journals. Close collaboration