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Networks (https://marie-sklodowska-curie-actions.ec.europa.eu/actions/doctoral-networks ). The Aalto Robot Learning Research Group (https://rl.aalto.fi ), part of the ENGAGE network, operates
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modeling, statistical approaches and machine learning. The successful candidates are expected to lead an outstanding independent research program that complements and extends the existing research efforts
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mathematics or a related field. The successful candidate will have expertise in at least in one of: Machine learning in the context of physical systems AI-based condition monitoring Reinforcement learning
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to deploy machine learning to support data analytics and complex decision-making processes. Knowledge of modern SW-tools in the area of energy and sustainability is highly beneficial. Your role and goals You
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researchers in applied mathematics and machine learning. This is due to its remarkable flexibility, mathematical elegance, and as it has produced state-of-the-art results in many applications. As a leading
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a starting grant. You will also contribute to teaching on bachelor, master and doctoral level. The successful candidate should be prepared to teach courses in key areas such as computer architecture
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skills (e.g. Python, Julia) to merge concepts of chemical engineering, operations research and computer science, as you may also need to deploy machine learning to support data analytics and complex
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. The concept has lately gained increasing interest from researchers in applied mathematics and machine learning. This is due to its remarkable flexibility, mathematical elegance, and as it has produced state
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under multiple design and production constraints. In this position, you will have a chance to make an impact by connecting and developing the solid and structural mechanics or machine learning expertise
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active role in advancing the research projects of the MQS group. Our recent research has focused on the theory and applications of variational quantum algorithms and quantum machine learning. We also have