Position Details

- Based in the College of Engineering and Information Technology at the Mawson Lakes or Mount Gambier campus
- Full‑time, 12 month fixed term contract
- Salary Range: $82,838 - $111,384 per annum (plus 17% superannuation)
- Contribute to the development of the next generation of operational forest inventory technologies

Work that matters

This multidisciplinary project will require a highly motivated postdoctoral research associate who will help to develop the next generation of operational forest inventory methods.

The project combines unmanned aerial laser scanning (ULS), terrestrial and mobile laser scanning (TLS/MLS), statistical calibration‑transfer, and machine learning technologies to improve the estimation of forest structural attributes across plantation forest environments.

Building on recently developed methods for LiDAR fusion and calibration‑transfer, the successful applicant will investigate recent approaches for transferring detailed structural information from limited ground‑based LiDAR acquisitions to landscape‑scale aerial datasets. The research will contribute to scalable forest inventory systems supporting timber valuation, carbon accounting, forest monitoring, and precision forest management.

Responsibilities

- development of next‑generation calibration‑transfer and domain adaptation methods for multi‑platform LiDAR
- machine learning and statistical modelling of forest structural attributes (e.g., DBH, height, crown dimensions, biomass, and stem quality)
- uncertainty quantification and propagation in operational forest inventory
- development of transferable inventory models across species, sites, stand age, sensors,



and geographic regions
- automated tree detection, segmentation, and structural reconstruction
- integration of aerial, terrestrial, and mobile LiDAR with other sensing modalities
- publication of high‑impact journal papers and collaboration with forestry industry partners

Experience

- a PhD (or be close to completion) in Remote Sensing, Computer Vision, Forestry, Geomatics, Machine Learning, Spatial Statistics, or a closely related discipline
- demonstrated research experience in one or more of:
- LiDAR processing
- forest inventory
- photogrammetry
- machine learning
- computer vision
- geospatial analysis

- experience analysing large spatial datasets
- programming experience in Python, R, or MATLAB
- strong quantitative and statistical skills
- excellent written and oral communication skills

Our commitment to inclusion and diversity

We are committed to fostering a culture of inclusion where diversity is celebrated and everyone feels respected and valued. Adelaide University is an equal opportunity employer, committed to creating a safe, inclusive, and equitable workplace where everyone can thrive. We strongly encourage applications from Aboriginal and Torres Strait Islander peoples, people with disability, and people of all ages, genders, cultural backgrounds, sexual orientations, and gender identities. We are committed to supporting flexible working arrangements and providing reasonable adjustments throughout the recruitment process.

Applications welcomed from Australian or NZ citizens, Australian permanent residents and those who have the legal right to work in Australia for the term of appointment.

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📌 Remote Sensing Fellow (Mount Gambier)
🏢 The University of Adelaide
📍 Mount Gambier