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and technology. Engaging in solving a real-world problem requires a real solution to enhance housing resilience. Applying research skills to optimise and innovate AI-driven solutions for the housing
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in an innovative and interdisciplinary approach. A background in science and engineering or social science and policy analysis is desirable. Experience with systems modelling (e.g. system dynamics
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of up to three years. Exceptional progress and adherence to timelines may qualify students for a six-month completion scholarship. Selection for these scholarships involves a competitive process, with
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. For more information about the application process, email About the scholarship As the successful applicant you will complete your PhD in the field of organic photochemistry for advanced reprogrammable
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to 3.5 years. Apply and develop your research skills working with an experienced team of interdisciplinary researchers within Flinders University and SARDI. This inspiring project involves: Engineering the
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I supervise a wide range of PhD projects on experimental research into the electronic properties of novel quantum materials including topological insulators, graphene, and other atomically thin two-dimensional materials. I am interested in creating a low-power topological transistor, in which an...
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scholarship. Selection for these scholarships involves a competitive process, with shortlisted applicants notified of outcomes by November 2024. Scholarship Details Maximum number awarded 1 Eligible courses All
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to research in dementia or complex trait genomics Not receiving any other full PhD scholarship or stipend Application process Please contact us via the EOI form . Enrolment Requirements Recipients must complete
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collaboration from industry partners AgriTech Solutions and Hydrotech Monitoring Pty Ltd (trading as HTM Complete), both leaders in agricultural technology and decision-support systems across Far North Queensland
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finite element methods, which demand extensive data and are costly, PINNs embed governing physical laws directly into the learning process. This allows effective management of limited and noisy data