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Field
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Develop industrial process digital twin models based on the fusion of mechanistic and data-driven approaches. Develop predictive maintenance and fault diagnosis algorithms for critical equipment (e.g
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, reliability, and consistent behavior. Learning-based controllers can achieve high performance in complex and uncertain environments, yet ensuring predictable operation under distribution shifts, sensor noise
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demand forecasting or behavior modeling Computing & Data Systems Cloud computing (AWS, Azure, GCP) Big data pipelines, distributed computing, and geospatial data processing Python, R, SQL/NoSQL
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algorithms, and prototypical systems controlling complex energy systems like buildings, electricity distribution grids and thermal systems for a sustainable future. These systems coordinate distributed
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(for example insect-eye–inspired motion detectors for planetary landing and insect-inspired navigation algorithms) to evolutionary and neuromorphic approaches to autonomous control, as well as soft-robotic