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degree (honours) or master degree by research in either: mechanical engineering biomedical engineering chemical engineering civil engineering applied mathematics applied physics related disciplines
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applied mathematical modelling machine learning multi-fidelity modelling numerical methods. Demonstrated programming ability (MATLAB/Python/C++) and enthusiasm to learn PyTorch. Previous experience in one
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English language requirements. Completion of a bachelor (honours) degree or master degree by research in: civil engineering geotechnical engineering petroleum engineering mechanical engineering applied mathematics
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of the STAMP RSV Program, supported by the Stan Perron Charitable Foundation. The PhD candidate will play an important role in developing models of RSV transmission and vaccination efficacy to inform
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injection into a reservoir saturated by water from core scale up to the numerical cell or a reservoir is a challenge. For immiscible two-phase flow in layer-cake reservoirs, the models for pseudo relative
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from other quantitative disciplines – such as data science, mathematical statistics, actuarial science, public health, or psychology – who have strong quantitative skills and an interest in causal
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methods, including causal econometric analysis and predictive economic modelling, to assess the economic and distributional impacts of policy interventions across healthcare and disability service systems
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quantitative disciplines such as data science, mathematical statistics, actuarial science or public health or psychology with strong statistical training. You can check your eligibility with the PhD readiness
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health economics, labour economics, economics and econometrics. We will also consider other quantitative disciplines such as data science, mathematical statistics, actuarial science or public health
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in oceanography, geomorphology, hydrochemistry, geophysics, and mathematical modelling. Applicants must have completed (or be close to completing) an Honours or Masters degree in Hydrogeology, Water