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experimental characterisation methods. We are looking for applications from enthusiastic candidates. [PhD project description] Project title : Machine Learning-assisted Development of Highly Functional Organic
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PhD Opportunity: Machine learning-based kinetic modelling on the thermal decomposition of plastic waste via pyrolysis Job No.: 661850 Location: Clayton / Advanced Fuel Innovation premises in
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variational inequalities. The newly developed algorithms will be applied to large-scale optimisation problems arising in federated learning. The PhD student will work under the supervision of Dr Minh N. Dao
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top researchers in data science (UTS) and social sciences (WSU and ANU) to develop statistical machine learning solutions for social good. This 3.5-year PhD project focuses on addressing social
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To address this limitation, this project aims to develop an innovative fatigue damage model that incorporates detailed defect characteristics using machine learning and multiscale modeling. High
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We are seeking applicants interested in communication design, digital learning design and youth arts to undertake a PhD that exploring online frameworks for capturing learning experiences in youth
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Join our multidisciplinary research team to develop and apply machine learning and bioinformatic algorithms in biomedical research. This PhD project will focus on developing machine learning
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PhD Project – Supervised and knowledge-guided machine learning approaches for quantifying and identifying microorganisms in water and wastewater treatment Job No.: 648559 Location: Clayton campus
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-class or H1 honours degree in Computer Science, Engineering or equivalent in a related discipline. Applicants must satisfy RMIT University’s PhD entry requirements. Applicants must have a first-class or
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) before the human eye can see them. The principal aim of this PhD research program is to develop methods to improve the hyperspectral image classification using deep learning techniques. The developed