This position is offered through the ANU Computing Internship courses (COMP4820 / COMP8830).
Semester 2, 2026 applications open on Monday 18th May 2026 and close on Sunday 31st May 2026.
Company
Haizea Analytics specialises in providing rapid access to satellite data and derived services for managing natural resources, ecosystems, and natural hazards such as floods and fires. What sets Haizea apart from others is its capacity to develop customised services and tools that harness high-resolution Earth observation data in a highly responsive, scalable and cost-efficient way. This unique ability is achieved by combining many years of expertise in spatial environmental applications.
Project
Zonal statistics is one of the most common operations in geospatial analytics. Given a map divided into regions (for example, postcodes, farm paddocks, or river catchments) and a gridded dataset covering the same area (for example, rainfall, temperature, or vegetation cover), the task is to compute a summary value (mean, sum, percentile, etc.) of the gridded data inside each region. As the volume and resolution of geospatial data we work with continues to grow, we want to invest in a more scalable approach, particularly for workloads involving high-resolution grids, regions with complex shapes, and multiple datasets covering all of Australia. There’s also an opportunity to take advantage of modern chunked storage formats like Zarr, which are well-suited to this kind of large-scale, parallel aggregation.
The intern will work on designing and building an efficient, reusable zonal statistics pipeline. That means getting familiar with Zarr and the trade-offs it introduces, then implementing a generic zonal stats tool against some of our existing datasets, with a focus on minimising redundant work when the same grid is queried against many different sets of regions. Once the core implementation is in place, the next step is to parallelise it using distributed compute on our local infrastructure and benchmark it against existing tools.
The project is a good fit for someone who enjoys performance and systems work and is comfortable writing clean, reusable Python. Geospatial experience is a plus but not a requirement. We’re happy to bring you up to speed on the domain side if you’re willing to learn.
Required technical skills
Required skills
- Python (proficient) — writing clean, modular code and reasoning about performance
- Comfort with the scientific Python stack (NumPy, and ideally pandas or xarray)
- Some experience profiling or benchmarking code
Preferred skills
- Familiarity with geospatial data formats (GeoTIFF, NetCDF, shapefiles) and libraries such as rasterio, geopandas, xarray, or rioxarray
- Experience with distributed computing
- Comfortable working on Linux
- Familiarity with Git
Required/preferred professional and other skills
Required:
- Good written and verbal communication. We’d like you to document what you build and explain your benchmarking results clearly
- Self-directed and comfortable working on open-ended engineering problems
- Willing to dig into technical specifications (including the Zarr v3 spec) and turn them into working code
Preferred:
- Interest in geospatial, earth observation, or environmental applications, or a willingness to learn the domain
Delivery Mode
In-Person
Student location
Canberra
Project’s Special Requirements/ Conditions
None
Type of internship
Paid internship - the student will be engaged as an employee
How to apply
Applications are invited from eligible students to apply for the Computing Internship courses COMP4820 or COMP8830. Eligibility details of COMP4820 / COMP8830 and further information about the Computing Internship can be found on the Computing Internship page.
Eligible students can apply through the Computing Internship application form which will be available via the Computing Internship page between Monday 18th May 2026 and close on Sunday 31st May 2026.
You can nominate multiple preferred Internship projects and host organisations through the one online application form.
Eligibility and room available in degree to undertake COMP4820/COMP8830 will be assessed at the time of application. If you do not meet the eligibility criteria or do not have room in your degree to fit COMP4820/COMP8830, your application will not be progressed.
Your application will require you to upload the following documents:
- an updated copy of your resume, and
- an expression of interest (limit 350 words) for each organisation you wish to apply to (organisations with multiple projects may only submit one expression of interest, so state clearly which project/s you wish to be considered for).