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the many good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as
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develop methodologies (such as acoustic emission method) detecting early signs of damage, leaks, or degradation before they become critical. We will also leverage the latest developments in machine learning
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Subject area: Drug Discovery, Sustainability, Laboratory Automation, Microfluidics, Machine Learning Overview: This highly interdisciplinary 4-year funded PhD studentship will contribute to cutting
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approach that integrates machine learning algorithms, blockchain technology, and IoT devices with digital twin systems. The scientific objectives of the project are as follows: Objective 1: Investigate how
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shaving/shifting, voltage and frequency support, and virtual inertial response. Due to the volatile and intermittent nature of RESs, in this project, machine learning (ML) methods are used to accurately
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training dataset of well-studied volcanoes with known large eruptions, the project will employ statistical and machine learning (ML) methods to identify the strongest predictors of eruption magnitude
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Start Date: Between 1 August 2026 and 1 July 2027 Introduction: This project fuses machine learning (ML) based inverse design approaches and topology optimisation (TO) to realise multiscale
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the state-of-the-art wind tunnel facilities of the Department of Aeronautics, and will utilize novel theoretical and machine learning tools. You can expect to become an expert in aerodynamics and turbulent
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for their employability in applications. Additionally, machine learning methods need to be applicable to high-dimensional and to noisy data that are typically encountered in real-world applications. The aim of this project
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the University of Liverpool. As well as gaining a formal HE teaching qualification, you’ll learn key pedagogical skills for the academic job market, primarily through shadowing mentored classroom involvement