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, they are ill-suited for inference about system's health in rapidly changing environment of wind turbines. Although physical laws can be enforced to learn a model whose parameters can be physically interpreted
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Do you want to be part of a young, dynamic research group working on designing the next generation of sustainable energy materials using computational chemistry and machine learning? And do you see
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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 research
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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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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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on reinforcement learning (RL) for policy discovery in a multi-sector “integrated modeling environment” that connects fast ML metamodels of simulators (e.g., transport, energy, environment, climate events). The aim
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for candidates with strong analytical skills, curiosity, and enthusiasm for cryptographic research. A solid background in theoretical computer science, mathematics, or a related field will be considered an asset
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on Problem Based Learning, with projects making up half the teaching at all semesters. Your competencies A relevant educational background within biology or a similar area is required. We seek a candidate with
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our group, you get the opportunity to use the latest algorithms in machine learning for improving
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-species interaction in gas–liquid bioreactor platforms. Deliver scientific excellence through high-impact publications, dissemination and outreach. Teach and develop courses at BSc and MSc levels in