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Creativity Support in Generative AI The position is open for appointment as of October 2026, or soon hereafter. The position is a three-year role, located in the Department of Computer
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of Power-to-X processes for renewable fuel production. The project is primarily rooted in process engineering while also addressing the interaction between Power-to-X plants and the electrical grid. You will
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possible thereafter. The appointment is for a period of three years. The successful candidate will be enrolled in the PhD programme in Biomedical Engineering and Neuroscience at the Faculty of Medicine
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to prioritize causal genes and pathways. Characterizing cell-type-specific mechanisms linking genetic variation to insulin resistance and glucose dysregulation. Developing computational approaches for multi-omics
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on machine learning, AI security, and real-time embedded computing for cyber-physical systems, with a strong emphasis on the AI and trustworthiness side of the problem. The main activities include: Designing
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, Water Resources, Civil Engineering, Physics and Meteorology, Applied Mathematics, Computer Science/Engineering, or a comparable discipline. The MSc degree must be equivalent with the Danish MSc degree
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multi-fidelity modelling, your research will advance and integrate three core elements: (i) physics-based multi-fidelity structural models enabling high-resolution analysis at fatigue-prone hot-spots
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degree in computer science, mathematics, statistics, physics or relevant fields. Strong background in machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph
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• Participate in the department’s research environment • Complete a PhD training programme • Teach at one or more of the department programmes Your main task as a PhD student will be to develop and complete a PhD
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patterns representing health incidents and the development of privacy-preserving methods for visualizing health data. What you will gain: Strong expertise in statistical and computational methods for privacy