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electrical engineering, control engineering, computer science, applied mathematics or a related field. The successful candidate will have expertise in at least in one of: Machine learning in the context
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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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datasets with new products and when existing products change during operation The Doctoral Researcher is expected to focus on research on applying offline reinforcement learning to heavy machines. While
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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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, molecular and mesoscale level particle-based techniques, continuum modeling, statistical approaches and machine learning. The successful candidates are expected to lead an outstanding independent research
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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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to teach courses in key areas such as computer architecture, compilers, and other topics related to hardware and low-level programming. An excellent command of English is required for teaching. This position
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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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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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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