154 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" positions at Technical University of Denmark
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on the economic impacts of renewable energy based on econometric methods. The work to be undertaken is related to a project, which will draw on input-output models that are tailored to sub-national level data in
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will benefit from your analytical insight. Advanced NMR methods and computational data analysis will be compounded to accelerate the understanding of reaction pathways and improved use of desired rather
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-event data collection + feedback Assist with analyses and PowerPoint for ongoing projects. Support partner recruitment in our scaling phase (e.g., prospect research) SoMe knowledge is a plus but not a
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environmental data analysis - this position offers an exceptional opportunity to grow as a scientist. In RhizoTrack, you will work at the interface of microbiology, chemical ecology, and sustainable agriculture
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to determine instability growth rates and connect experimental data to theoretical models. The candidate will contribute to the design and implementation of key components, including helicon antennas for plasma
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The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the
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Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 16 months. You can read more about career paths at DTU here . Further information
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data designed to foster inclusive, efficient and seamless transport infrastructure and mobility services. Subsequently, you will further develop the perspectival modelling approach, bringing LLMs
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software and code changes. In the long term we are planning to supervise Bachelor/Master projects and potentially develop courses about effective use of large-scale Storage-, HPC-, cloud- and data management
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Division at DTU Management. The PhD project aims to analyze and optimize Hospital-at-Home concepts using data-driven decision-support addressing challenges like long distances to specialist care and high