44 data-"https:" "https:" "https:" "https:" "VIETNAMESE GERMAN UNIVERSITY" PhD positions at Monash University
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disability, and contributes directly to nationally significant health and disability policy reforms. The successful candidate will undertake data-driven, policy-relevant research using advanced quantitative
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labour markets shape the recruitment, retention, well-being of doctors and nurses, and how these dynamics affect access to care and population health. Using large-scale longitudinal administrative data and
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significant health and disability policy reforms. The successful candidate will undertake data-driven, policy-relevant research using advanced quantitative methods, including causal econometric analysis and
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, and how these dynamics affect access to care and population health. Using large-scale longitudinal administrative data and modern causal inference methods, the research will analyse how changes in pay
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health, employment, and wellbeing outcomes for individuals and families. The successful candidate will join a highly collaborative research team using linked employer–employee administrative data
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, or High Second-Class Masters degree or equivalent in the health-related field. Strong quantitative research skills. An understanding of quantitative research methodology and data analysis. Evidence of
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shape health, employment, and wellbeing outcomes for individuals and families. The successful candidate will join a highly collaborative research team using linked employer–employee administrative data
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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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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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measurements in particle physics. Many of my projects are informed directly by current measurements, e.g. addressing new or unexpected features seen in the data. Others focus on improving the formal accuracy