Machine learning for flood resilience

Machine learning for climate-induced flood resilience in Tasmania

Degree type

PhD

Closing date

1 October 2024

Campus

Hobart

Citizenship requirement

Domestic / International

About the research project

Help us better understand the future of climate resilience with this PhD opportunity focused on advancing flood projections and mapping in Tasmania, Australia. In the face of unprecedented climate challenges, ranging from heatwaves to droughts, understanding and mitigating the impacts of climate-induced floods is critical.

This project aims to take a multidisciplinary approach to transform flood mapping in specific Tasmanian regions. The overarching goal is to harness the power of advanced data analytics and machine learning techniques to predict and manage floods triggered by climate change. By combining comprehensive region studies, advanced machine learning model development, and innovative flood mapping with ArcGIS, this research seeks to contribute to a more resilient future.

This project is offered by the Climate Futures research group and forms part of a Disaster Ready Fund project funded by the Australian Government, A Natural Hazards Atlas for Tasmania: mapping natural hazards to build disaster resilience and preparedness. The PhD research forms part of this wider project which will for the first time assess multiple hazards across the state of Tasmania and will deliver a wide range of actionable climate and hazards information for a range of end-users in industry and government.

During this PhD research project you could be:

Analysing flood data, decoding climate mysteries and crafting solutions. You would be a data maestro, a field explorer, and a mapping wizard, all in one. Dive into the world of machine learning, unravel the secrets of climate patterns, and create maps that guide communities toward resilience. In this journey, you would not just be a student; you would be a hands-on researcher shaping the future of climate adaptation.

Possible PhD research questions could include:
*How accurate and reliable are the predictions made by the developed flood prediction model?
*What are the specific impacts of climate change on the frequency and intensity of floods in the Tasmanian region?
*How effective are flood mitigation strategies in reducing the vulnerability of communities to climate-induced floods?
*Can real-time flash flood mapping be achieved with high accuracy and efficiency?
Depending on your specific interests and expertise, there may be other related research questions that could be pursued as well. Please contact the primary supervisor/s to discuss.

Primary Supervisor

Meet Dr Kathleen Beyer

Funding

Applicants will be considered for a Research Training Program (RTP) scholarship or Tasmania Graduate Research Scholarship (TGRS) which, if successful, provides:

  • a living allowance stipend of $32,192 per annum (2024 rate, indexed annually) for 3.5 years
  • a relocation allowance of up to $2,000
  • a tuition fees offset covering the cost of tuition fees for up to four years (domestic applicants only)

If successful, international applicants will receive a University of Tasmania Fees Offset for up to four years.

As part of the application process you may indicate if you do not wish to be considered for scholarship funding.

Other funding opportunities and fees

For further information regarding other scholarships on offer, and the various fees of undertaking a research degree, please visit our Scholarships and fees on research degrees page.

Eligibility

Applicants should review the Higher Degree by Research minimum entry requirements.

Ensure your eligibility for the scholarship round by referring to our Key Dates.

Additional eligibility criteria specific to this project/scholarship:

  • Applicants must be able to undertake the project on-campus

Selection Criteria

The project is competitively assessed and awarded.  Selection is based on academic merit and suitability to the project as determined by the College.

Additional essential selection criteria specific to this project:

  • A background in climate science, hydrology, or a related field.
  • Familiarity with flood modelling and hydrological analysis.
  • Demonstrated expertise in machine learning techniques, with a focus on both supervised and unsupervised methods.
  • Strong skills in programming, data analysis a data visualisation (e.g. Python, R, Matlab, and similar languages)
  • Proficiency in spatial data analysis and GIS tools, particularly ArcGIS.
  • Experience with climate model data, including GCMs and RCMs.
  • Strong written and verbal communication skills.
  • Ability to work independently and as part of a team

Additional desirable selection criteria specific to this project:

  • Experience handling large datasets and familiarity with netCDF format.
  • Experience working with high performance computing.

Application process

  1. Select your project, and check that you meet the eligibility and selection criteria, including citizenship;
  2. Contact Dr Kathleen Beyer to discuss your suitability and the project's requirements; and
  3. In your application:
    • Copy and paste the title of the project from this advertisement into your application. If you don’t correctly do this your application may be rejected.
    • Submit a signed supervisory support form, a CV including contact details of 2 referees and your project research proposal.
  4. Apply prior to 1 October 2024.

Full details of the application process can be found under the 'How to apply' section of the Research Degrees website.

Following the closing date applications will be assessed within the College. Applicants should expect to receive notification of the outcome by email by the advertised outcome date.

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