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research in peer-reviewed journals and presenting at international conferences We are looking for a candidate with: A PhD in oceanography, climate science, applied mathematics, computational science, or a
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-field, and field-scale research facilities, advanced computing capacities as well as an extensive national and international researcher network. The department consists of eight research sections with
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contribute to the teaching activities of the section of Mechanical Engineering by teaching 1-2 courses per semester. You will focus on developing and extending in-house computational codes based on open-source
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of national and European research projects and enjoys a robust network of academic and industrial partners. This position provides an opportunity to engage with these collaborations and work on real
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. The position is part of a project funded by the Energy Technology Development & Demonstration Programme (EUDP). The project is led by Associate Professor Jonas Sundberg and is an interdisciplinary collaboration
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in combination with computational biology approaches to generate comprehensive models of gene regulation during development and diseases such as cancer and neurodevelopmental disorders. To learn more
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experimental research facilities and technologies, situated in close connection to the research environment, and a comprehensive national and international research network and good industrial and professional
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experimental research facilities and technologies, situated in close connection to the research environment, and a comprehensive national and international research network and good industrial and professional
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industrial and academic partners. The overall goal of the project is to optimize the design of water eletrolyzers for efficient green energy production. You will be conducting Computational Fluid Dynamic (CFD
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2-yr postdoc on Forecasting Biosphere-Scale Effects of Ecological Novelty Using Species Distribut...
Aarhus University. Key international associates to ECONOVO will also be involved. ECONOVO and ECOINF form a cooperative, interdisciplinary research network with extensive international involvement