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disciplines, and data science seeks to build models and extract meaningful information from large amounts of complex data. Machine learning, artificial intelligence and data-drivenness cut across all our
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-scale simulation, signal and image processing, time-series analysis, optimization and control, computational inverse problems, and artificial intelligence methodologies. The field of teaching is
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integrated circuit design. Possible focus areas can include, but are not limited to, machine learning (ML), Artificial Intelligence (AI), neuromorphic computing, and digital signal processing hardware
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care sector or in a business environment and using and teaching different types of simulation tools and artificial intelligence is considered as an advantage. Success in teaching requires good
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experience in at least 2 of the following areas: quantitative analysis, ML and Data Science, artificial intelligence (AI), innovation studies, with a strong track record. Capability to learn and develop your
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civil engineering, materials engineering, computer science or applied artificial intelligence. Related scientific publications are a plus. Excellent communication skills in English are required, and
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be used in many different applications, such as optical communication, computing, sensing and imaging. It is also linked to artificial intelligence and quantum technologies. We believe that PIC