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Field
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diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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We are currently offering a PhD student position focused on developing new AI-driven methods for molecular engineering, with an emphasis on the discovery and design of solid polymer electrolytes
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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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challenging molecular engineering problems in life sciences and materials design. Situated in the Data Science and AI division, our group advances generative models, molecular simulations, and molecular design
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Australian Research Council (ARC) Funded PhD Opportunity at Faculty of Engineering: High-Speed Rail and Sustainable City Sizes in Australia Location: Clayton campus Department/Unit: Monash Institute
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If you are ready to launch your research career in advanced manufacturing and want to build cutting-edge skills in AI and real-time data-driven production, this PhD opportunity is your gateway. As
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diverse backgrounds (e.g., economics, engineering, computer science, information systems, etc.), united in pursuit of sustainable solutions that positively impact and shape a low-carbon economy and society
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Qualification: The candidate should possess a MSc. Degree or equivalent in Engineering, Computer Science, or related fields. Experience: The ideal candidate should have some knowledge and experience
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, convective exchange with the environment, biochemical quality attribute evolution within the products, and thermally-driven damage (chilling-freezing injury). Use these models to build physics-based digital