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computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics
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(density functional theory and ab-initio molecular dynamics simulations) with artificial intelligence techniques to parameterize machine learning force fields and kinetic Monte Carlo methods to model
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have a long-term involvement in applied and interdisciplinary research, big data and data science, artificial intelligence (AI), the Internet of Things (IoT), smart and secure societies, smart
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strategies for energy storage and production across transmission and distribution networks. Digital methodologies and solutions that support the transition of energy systems towards sustainability (artificial
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and data science, artificial intelligence (AI), the Internet of Things (IoT), smart and secure societies, smart manufacturing, and life sciences. We also collaborate with other universities, external
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applied and interdisciplinary research, big data and data science, artificial intelligence (AI), the Internet of Things (IoT), smart and secure societies, smart manufacturing, and life sciences. We also
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interdisciplinary research, big data and data science, artificial intelligence (AI), the Internet of Things (IoT), smart and secure societies, smart manufacturing, and life sciences. We also collaborate with other
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robotics, visual perception, and artificial intelligence in laboratory environments. The goal of this project is to enhance the capabilities of robots by means of advanced computer vision, enabling them
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endogenously by CRISRP, subcellular localization of proteins by spatial proteomics and fluorescence microscopy, and protein structure prediction by artificial intelligence-based strategies combined with
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. Qualifications and Requirements A master’s degree (or equivalent) in Marine Biology or Engineering with computational experience, Computer Science, Artificial Intelligence, Data Science, or a related field