Using Data to Overcome Wellbeing Challenges Across the Life Spectrum

Follow this link to apply

PhD Scholarship Applications now open!

Deadline 24 October 2021

For January or April 2022 start

 

About the Project

The World Health Organization refers to obesity as a global epidemic. It is an issue across all ages, but the cost becomes far greater in older years and thus the value for addressing it is greatest in children. This research will collaborate with leading experts from Health & Wellbeing Queensland to build new data platforms, using obesity data as an exemplar, across the life course and linking it with clinical data from hospital care (from Queensland’s new EMR implementation) as well as population health and community data. It will involve attention to the careful curation of data from different Government departments and services.

This project will look at case studies across three diverse settings – urban, rural and remote, to determine what datasets are useful in describing population health; what predictive modelling techniques are useful in describing the current and future state of communities and individuals within the community; and how to best engage and impart information to and with clinicians – from primary through to tertiary care institutions – to utilise the knowledge to drive precision prevention practice change that will meet and overcome the growing burden of chronic disease in  our society.

 

About the Candidate

This is an opportunity for a highly motivated student to join the CIRES project team, collaborating closely with leading experts in Health & Wellbeing Queensland to apply predictive modelling to datasets for useful insights into communities to drive innovation and change in clinical settings.

For this project, CIRES is seeking a candidate with interdisciplinary interests and capabilities. The candidate will have qualifications relevant to this project, e.g., Master of Data Science, Computer Science, IT, and/or Bachelor of Computer Science, IT, Mathematics. Qualifications in other disciplines (e.g., health science) with demonstrable expertise in solving data-driven problems are also welcome. 

The candidate will have hands-on experience with data science, data analytics, or machine learning tasks, preferably with expertise in predictive analytics, knowledge graph mining, and causal inference. Meanwhile, candidates with a science background, like nutrition, diet, and public health but with a data-driven skillset, also align with the scope of this project.

Proficiency in Python programming language and machine learning software packages such as Tensorflow and Pytorch is required.

 

PhD Scholarship Applications now open!

Deadline 24 October 2021

For January or April 2022 start

Follow this link to apply

project researchers
Prof Andrew Burton-Jones
Dr Rocky Chen
Prof Shazia Sadiq
A/Prof Hongzhi Yin (Principal Advisor)
partner investigator
Health + Wellbeing QLD