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scholarship is available at the Institute for Frontier Materials (IFM), Deakin University. This project will develop solid electrolytes using combined machine learning (ML), molecular modelling, and
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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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Overview Join us to make a difference! A highly competitive scholarship to develop new statistical machine learning and data-driven methods to battle social disadvantage in NSW. You will work with
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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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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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machine learning to identify meteorites in aerial imagery, with great success, and recovered multiple meteorites using a UAV. This project will build on this success, by extending the drone approach to new
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on leveraging advanced computer vision (CV) and deep learning (DL) techniques to develop a state-of-the-art computer-aided detection and diagnosis (CAD) system for early-stage Alzheimer's disease (AD) detection
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the following knowledge and/or experience are highly preferred: Computer Vision, Signal Processing, Machine Learning knowledge and/or; Experience Industry knowledge and/or; A track record of published
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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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The PhD candidate will gain intensive knowledge in innovative processing protocols for chemical sensing and to develop data acquisition system with the Machine Learning (ML) and/or Deep Learning (DL