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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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expected to engage in deep collaboration with research groups at Faculty of Science and Faculty of Pharmacy to enhance cutting edge research in the area. The focus of the position is on application and
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entails teaching responsibilities within automation of synthetic chemistry and high-throughput experimentation. We seek candidates who demonstrate a collegial approach to teaching and a deep appreciation
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candidates who demonstrate a collegial approach to teaching and a deep appreciation for the societal role of university education. As a matter of strategic decision, Department of Chemistry has acquired a
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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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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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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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record and familiarity with the existing literature and research in the field of statistical machine learning, and deep learning or large language models. Possess sufficient specialist knowledge, research
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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