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Post Doctoral Researcher in Digital Twins CO2-to-Protein production in collaboration between the ...
In the intersection between combatting climate change and world hunger, a new technology has emerged that enables food (protein) to be made from air (CO2) using nature’s own principles. The novel
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In the intersection between combatting climate change and world hunger, a new technology has emerged that enables food (protein) to be made from air (CO2) using nature’s own principles. The novel
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when imaginaries shape collective action toward climate change solutions, how they are collectively constructed and negotiated among multiple actors, and how they impact societal transformation
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possible thereafter. The position will be available for a 2-year period. Wetland restoration is increasingly promoted as a nature-based solution to climate change and biodiversity loss. However, the long
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, through developing predictive models and new experimental methods and instrumentation, to design creative and cost effective CO2 trapping processes. The need is urgent, the task is challenging and a
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Applications are invited for a 2-year position in the field of CFD and modeling of heat pumps at the Department of Mechanical and Production Engineering, Aarhus University, Denmark. Expected start
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Applications are invited for a 2-year position in the field of CFD and modeling of heat pumps at the Department of Mechanical and Production Engineering, Aarhus University, Denmark. Expected start
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language models (LLMs) for educational purposes. Furthermore, the right candidate has a deep understanding of pedagogical research, with focus on how educational processes can be facilitated by AI. The role
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domains. The scientific outcomes are expected to be significant in: Earth system science – by improving models of Earth surface evolution and enabling better predictions of landscape response to climate
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industrial domains. The scientific outcomes are expected to be significant in: Earth system science – by improving models of Earth surface evolution and enabling better predictions of landscape response