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(Human-AI symbiosis as a means to tackle societal challenges). Symbiosis takes an interdisciplinary approach to address the opportunities, challenges, and risks associated with the use of AI in one
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for the automatic generation of future energy technology scenarios based on LLMs, patent data, and scientific literature Investigating the system-level conditions under which future technologies like fusion and
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minimise observer variability, leading to more reliable and accurate predictions of patient outcomes. Furthermore, integrating AI-assisted frailty assessments into surgical risk scores can provide a
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grades in the field of mechanical engineering, material science, physics, computational science or similar, preferably with a specialization in the field of theory and/or simulation Strong understanding
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stability. However, the fine-grained monitoring needed for such coordination risks exposing privacy. Although operators collect this information to ensure reliability, current practices seldom embed strong
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of global trends and technology-specific impacts on electricity production Integration of projected volatile electricity production into existing energy system models along with an assessment of how climate
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performed under this internship by an Electrical/Power Engineering PhD student would support AEMO with assessing key non-credible contingency risks in future scenarios and could include: Supporting complex
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opportunity in composites materials for space application research in the Composites and Advanced Materials Centre and the Centre for Defence Engineering at Cranfield university. The focus of this PhD will be
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Job Description The Faculty of Engineering at the University of Southern Denmark (SDU) invites applications for one or more 3-year positions as a Ph.D. in Control of electric machines using WBG