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computational analysis/simulation in at least one of the above areas. Familiarity with the application of Artificial Intelligence, Machine Learning and/or Data Analytics in Aircraft Propulsion and related areas
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the development of climate change models of fashion supply chains and the design of computer model laboratory experiments (with students) that will aim to determine what and how participants learn from these models
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Engineering Work Location Lexington, KY Type of Position Faculty Position Time Status Full-Time Tenure Track Status Tenure Track Required Education PhD Required Related Experience N/A Required License
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: Department of Electrical & Computer Engineering Term: Winter 2026 Course subject code: ECSE 552 Course Title: Deep Learning Course Credits: 4 credits Location: ENGMD 279 Schedule: Monday and Wednesday: 8:35 am
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learning, artificial intelligence, and related topics. Additionally, this position will provide support for the PhD program in Data Science and Engineering, which is shared by the Departments
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archiving and preservation, network analysis and social media analytics, and human-computer interaction in humanities contexts. The National University of Singapore (NUS) is a leading research-intensive
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experiments and cognitive modelling. You will focus on machine learning, but will be involved in all areas. There are also spinout opportunities. For details: PhD information sheet The team have wide experience
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, that consumers still enjoy. By developing novel, cutting-edge technological approaches including computer vision, machine learning and robotics, blended with consumer science, you will be at the forefront
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where all team members can thrive. We offer a stimulating research and learning environment with advanced PhD courses in areas such as optimal control, machine learning, and probability theory
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stimulating research and learning environment with advanced PhD courses in areas such as optimal control, machine learning, and probability theory. The working language is English, and our team is international