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Master’s and PhD thesis opportunities with the BODE³ Programme

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Are you interested in public health and prevention? Specifically encouraging healthy eating, reducing obesity, and preventing chronic diseases? Are you interested in which interventions not only improve health, but also reduce health inequalities, make better use of health dollars, and maybe (just maybe) improve workforce productivity so the retirement age can be lifted? Are you interested in epidemiological methods underlying simulating disease intervention impact on future health gains and costs?

Would you like to deepen your epidemiological and simulation modelling skills? Want to know how to estimate the cost-effectiveness of preventive interventions? Passionate about converting rich NZ (big) data into useful information for decision-making?

If the above interests you, then BODE3 may have a master’s or PhD thesis option for you. To fit with us, you will need to have a strong academic record – most likely with demonstrated strength in quantitative analysis (e.g. epidemiology, computer science, engineering, statistics, economics). You will need to have a GPA average in excess of 7.5 according to the University of Otago GPA calculator. You will also need to be a New Zealand or Australian citizen or resident – or intending to become one.

You will be supervised by academics with expertise in one or more of: epidemiological methods; simulation modelling (Markov, multistate lifetables); economics; nutrition; tobacco control; big data; costings and cost data; and public health generally (we have wide research interests – see the publications on our website).

Our work environment is stimulating and you will be sharing office space with other master’s and PhD candidates.


The topic areas below are ones that we invite PhD thesis enquiries about. We also welcome novel suggestions for thesis topics that align with our funded work programme (eg, also in the domains of tobacco and vaping).

1. Machine learning and equity in improving health (Master of Public Health)

Artificial intelligence (AI) and machine learning pose enormous potential for improving quality of life but also significant social, cultural and other risks. It is therefore crucial to ensure that machine learning models do not create or exacerbate inequities in healthcare, due to biased data and unfair algorithms. In Aotearoa New Zealand, diabetes and cardiovascular diseases are the leading causes of premature death and disease burden and major sources of health inequities for Māori, Pacific, and Asian populations due to socio-economic, cultural and health system factors.

We are looking for a Master of Public Health student to join our project Predicting risk of diabetes complications and costs using machine learning with equity analysis funded by the Royal Society Te Apārangi. The research topic is using Aotearoa’s rich social and health datasets to build equity into the machine learning models, and predict cardiovascular disease risk and healthcare costs among people with diabetes. The project will partially cover Master’s stipend and tuition fees.

Student applicants will need to have a strong academic record and high motivation. If you are interested in this topic, please send a copy of your CV, academic transcripts and cover letter to Dr Nhung Nghiem (

2. How much does it cost? The health system and productivity? (PhD)

Are you interested in the intersection of epidemiology and costing? For example, how much would a tobacco tax intervention cost, or save costs, to: the health system; to the labour market (productivity costs); and for welfare benefits (including superannuation payments because people live longer…).

In BODE3 we are harnessing extraordinarily rich health data linked to not only health system cost data, but also to income data (for productivity costing) and welfare benefit receipt (for sickness benefits and superannuation payments). This is a unique opportunity internationally, let alone in NZ, to make real strides in understanding the societal impacts of public health interventions. You will have ample opportunity to publish. Your supervision will start from an epidemiological basis (one needs to have the epidemiology right first, before working out the future stream of people living, dying and living in poor health), but with strong additional disciplinary input from economics.

For more information contact Professor Tony Blakely ( Send a copy of your CV, academic transcripts and cover letter, in addition to an overview of your interest in this PhD thesis opportunity.

3. Epidemiology meets demography, simulation modelling and economic decision-making (PhD)

In recent years there have been surges in methods and applications of simulation modelling (e.g. the impact of tobacco tax on future mortality rates), in parallel with counterfactual analytical approaches to causal inference and mediation (e.g. how much of the association of ethnicity with mortality is mediated by tobacco?). Often at the heart of simulation modelling of public health interventions are structural relationships of variables – causal webs. But do we get it right? Do we get the effect sizes on each ‘arrow’ correct? How can we do better? And does it make much difference to modelled outputs (e.g. change in mortality rates from a tax, and change in inequalities)?

As longevity improves, public health needs to focus more on quality of life – especially around the retirement age to ensure society can afford to support a longer living population. Which begs the question as to which health interventions not only extend quantity and quality of life, but also workforce productivity. To answer such questions requires a degree of sophistication and accuracy in simulation models that is not usually expected; can we do this?

For more information contact Professor Tony Blakely ( Send a copy of your CV, academic transcripts and cover letter, in addition to an overview of your interest in this PhD thesis opportunity.

4. Pre-diabetes modelling (PhD)

We are currently modifying the current BODE3 DIET/Physical activity to a pre-diabetic population. The range of evaluations that could be evaluated is large. There are also methodological extensions that will make good components of a PhD. If you are interested in this important health topic and related modelling, , then contact Dr Cristina Cleghorn ( Send a copy of your CV, academic transcripts and cover letter, in addition to an overview of your interest in this PhD thesis opportunity.

5. Quantification of the greenhouse gas emissions changes associated with reductions in healthcare spending

BODE3 has modelled the health impacts and cost-effectiveness of numerous interventions from tobacco control to salt reduction. These sophisticated multi-state life-table models provide outputs in terms of quality-adjusted life-years (QALYs) gained and health system costs. Increasingly, the models have expanded to cover wider societal impacts such as productivity costs and greenhouse gas emissions associated with specific interventions (e.g. reducing car use).

Recent research has demonstrated that the healthcare system may account for a considerable proportion of greenhouse gas emissions at the national level (10% in the USA, 7% in Australia). Interventions that reduce healthcare spending could therefore help to reduce greenhouse gas emissions, but this needs to be balanced against other contributors to net greenhouse gas emissions such as usual citizen emissions from being healthy and living longer.

We are looking for an enthusiastic and motivated student to complete a PhD in this area. The student will be expected to identify the main contributors to greenhouse gas emissions from healthcare in the NZ context, calculate the emissions impacts associated with different disease states to incorporate into existing models, and then quantify the greenhouse gas impacts associated with specific healthcare and preventative interventions.

If you are interested in quantifying the greenhouse gas emissions associated with health interventions, then contact Dr Anja Mizdrak ( Send a copy of your CV, academic transcripts and cover letter, in addition to an overview of your interest in this PhD thesis opportunity.