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hydrogen storage, downstream processes, and energy demand, to enable more efficient, flexible, and economically viable Power-to-X operation. This position is expected to start from 1st of November 2026 or as
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solutions that combine low energy consumption with reliable and safe operation in compliance with relevant standards and regulatory requirements. A key scientific challenge addressed in this project is the
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interactions with CSE activities. Please find guidelines and further information on the website of the PhD School: https://www.cbs.dk/en/research/phd-programmes/admission . Recruitment procedure The Recruitment
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for one fixed operating point and cannot adapt when grid conditions change. In this project you change how carbon-aware AI is designed. Instead of producing a single “best” model, you will use neural
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related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with deep learning, computer vision, medical image analysis
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universities. The transition towards electrified and energy-efficient energy systems poses significant challenges in predicting the coupled behaviour of thermofluid, electromagnetic, and rotordynamic processes
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process at https://employment.ku.dk/faculty/recruitment-process/ . For more information on working and living in Denmark, please visit http://ism.ku.dk (International Staff Mobility) and https
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in the interplay between wireless systems and Artificial Intelligence. Experience with one or more of machine learning, wireless communications, signal processing, multimodal sensing, robotic
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: https://healthsciences.ku.dk/phd/guidelines/ Application procedure Your application must be submitted electronically by clicking ‘Apply now’ below. The application must include the following documents in
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datasets, the project seeks to bridge the gap between disease-associated genetic variants and the biological processes they influence. The successful candidate will leverage unique resources available