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This PhD project will develop intelligent, data-driven methods that enable electric vehicles (EVs) to serve as mobile energy storage while remaining readily available for transportation
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Required knowledge Skills Focus proficiency in one programming language (e.g. Matlab, R, Python), machine learning / deep learning / data science skills, basic understanding of cell and development
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an important part of a Monash AI institute collaboration between the Arts and IT faculties around technology for orientation and mobility for Blind and Low Vision people. The PhD project will undertake
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experimental validation. Established datasets and simulation environments can be used for systematic benchmarking, followed by deployment on humanoid or mobile robots using NVIDIA Jetson edge computing platforms
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. Selected methods can then be evaluated through real-world human-robot interaction using humanoid and mobile robotic platforms. Aim/outline The aim of this project is to develop multimodal world models
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The project involves building and curating a comprehensive food image dataset suitable for mobile AI applications. High-accuracy deep learning models will be trained on this dataset and then
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On-device machine learning (ML) is rapidly gaining popularity on mobile devices. Mobile developers can use on-device ML to enable ML features at users’ mobile devices, such as face recognition
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Mobile and continuous health monitoring has seen major advancements in recent years. The capabilities of current mobile phones and their built-in sensors have inspired many mobile sensing
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well-being and mental health, to the future of music, and inclusive communications for CALD communities – we have an exciting research program for those ready to take the next step in their career and
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damage from disease and injury. We are looking for recruits whose research program that align with any of the current research themes at ARMI: https://armi.org.au/our-groups/ Heart and Muscle Development