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artificial intelligence, architectural design, or a related field. We welcome candidates from diverse backgrounds, demonstrating strong collaboration skills and the ability to acquire new skills and
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. Relevant contexts may include, for example, neighbourhoods undergoing urban transformation, historic city centres, post-industrial areas, housing estate areas, peripheral urban settings or public places
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innovation, knowledge sharing, and professional development. Learn more about AAU Energy at www.energy.aau.dk. How to apply Your application must include the following: Application, stating reasons
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statistics This PhD project falls under the collaboration between Research Thrust RT2 Physics-based models, and Research Thrust RT3 on representation, compression, learning, and inference. For long-distance
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electrical energy storage systems; energy management systems. Experience with data processing, statistical analysis and machine learning techniques is an advantage. Knowledge with Mathworks suite, C/C++ and
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for a curious and engaged colleague with a genuine interest in the research topic. You enjoy working analytically with quantitative data, approaching research questions thoughtfully, and learning new
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collaborative environment that supports innovation, knowledge sharing, and professional development. Learn more about AAU Energy at www.energy.aau.dk . How to apply Your application must include the following
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the person listed at the bottom of the job posting. Interviews are expected to be held in April 2026. Further information Read more about our recruitment process here. The assessment of candidates
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% of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique
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to multi-task learning for multi-cancer risk prediction. To develop these models, you will have access to unique biobank data containing genetic information linked to Danish registry data for approximately