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: ……………………………………………………………………….………..…………………..……… 1. Enrollment in a PhD program in the areas indicated above at the University of Madeira. 2. Preferred requirements: experience in data science and artificial intelligence; experience in research
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high-quality research in one of the Department's key research areas: (i) Artificial Intelligence and Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition
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applied applied artificial intelligence for industry applications as well as publications in top-tier international conferences and journals, as well as real-world implementations. If interested, please
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support for process development from laboratory to pilot to demonstration scale Working with a wide range of simulation tools such as CFD, numerial optimisation and artificial intelligence Topic-independent
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interdisciplinary methods (such as artificial intelligence, digital twins, AR/VR, operations research, human factors, structural health monitoring, robotics) in the research focus of Industrialized Construction
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, cybersecurity, urban informatics, data sciences, artificial intelligence, renewable energy, and health, among others. Our faculty and students are part of the high-tech start-up culture in New York City and in
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interactions with local centres of excellence in artificial intelligence, machine learning, applied mathematics, and computational sciences Application Procedure We accept applications from students of any
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Informatics or in a closely related field such as Artificial Intelligence, Data Science, Computer Science, or Software Engineering, with an application focus in the energy domain. We seek candidates with
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are no longer sufficient to explore the vast chemical space of recycling streams. To overcome this, "AI-Powered Microfluidics" - the synergy between microscale fluidics and Artificial Intelligence - offers a
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for Artificial Intelligence. The position aims to strengthen methodological and algorithmic work on one or more of the following axes: Optimization and learning on very large models and datasets, improving