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Advanced statistical modeling and machine learning for health economics

Sydney
beBeeData
Posted: 15 August
Offer description

Prestigious Scientia PhD Scholarship

We are seeking a highly motivated and talented individual to join our team as a PhD Scholar on Panel Data Methods and Models.

As a member of our research group, you will be affiliated with the Australian Research Council (ARC) Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS) and have access to its resources. You will also gain exposure to a range of development opportunities across research, teaching, learning, leadership, and engagement.

The successful applicant(s) will have the opportunity to work with a supervisory team that includes leading academics in the field, and contribute to the development of novel statistical methods motivated by analyzing individuals responding to changes in their work and personal environments. Key questions involve socio-economic disparities in healthcare treatment and financial burdens following health shocks, best answered using panel data to track individuals over time.

For more information about this project and how to apply, please visit our website or contact us directly. We look forward to hearing from you!


Key Responsibilities:

* Conduct advanced research in panel data methods and models under the supervision of leading academics in the field.
* Develop novel statistical methods motivated by analyzing individuals responding to changes in their work and personal environments.
* Contribute to the development of the UNSW Scientia PhD Scholarship Scheme.


Required Skills and Qualifications:

* PhD in Statistics, Economics, Mathematics, or related field.
* Strong background in statistical modeling and computational skills.
* Excellent communication and teamwork skills.


Benefits:

* Tax-free stipend of $40,000 per annum.
* Travel and development support package of up to $10,000 per annum.
* International students: tuition fee scholarship.


Others:

* Access to a range of development opportunities across research, teaching, learning, leadership, and engagement.
* Affiliation with the ARC Centre of Excellence for Mathematical and Statistical Frontiers (ACEMS).

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