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Field
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and Applied Sciences Department/Area Electrical Engineering/Computer Engineering/Computer Science Position Description Project Deep learning plays an essential role in the operation of an autonomous
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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
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SIT's mission is centred on nurturing industry-ready graduates who possess deep technical expertise and transferable skills to address future challenges. We collaborate with industry in our
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SIT's mission is centred on nurturing industry-ready graduates who possess deep technical expertise and transferable skills to address future challenges. We collaborate with industry in our
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leadership in teaching and learning. This is a Full Time, Fixed Term position available for a period of up to 5 years at the classification of Level D. The full-time equivalent salary range is $161,351.44
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
leadership, and grant funders. These postdoctoral positions offer project management learning opportunities for recent PhD recipients who want to interpret the meaning and importance of engaged humanities
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Responsibilities: Development of stochastic and analytical methods for nonlinear partial differential equations Implementation of relevant numerical experiments using deep learning algorithms Job Requirements: PhD
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, machine learning, AI, or related field. Developing expertise in data science and machine learning, focusing on health-related applications. Proficient in machine learning, AI techniques (deep learning
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-time fault prediction. ML models, such as deep learning, reinforcement learning, and ensemble techniques, can analyze large-scale operational datasets from hydroelectric power plants, identifying
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health data, such as electronic health records or biobank-scale resources (e.g., UK Biobank, All-of-Us, FinnGen). Familiarity with machine learning approaches, such as penalised regression, deep learning