Jobs and Careers

• A highly motivated geospatial scientist with expertise in drone remote sensing
• Contribute to a nationally significant biodiversity monitoring initiative
• Full time, fixed term role until December 2026

About the opportunity

Join the NatureScan project (funded by the Department of Climate Change, Energy, and the Environment and Water – DCCEEW), a collaboration between the University of Tasmania and the TERN Surveillance Team at the University of Adelaide. The aim of the project is to advance national biodiversity monitoring through drone-derived observations. In close partnership with two existing project staff members, a Research Associate in Drone Remote Sensing (UTAS) and a Research Associate in Field Ecology (UoA TERN), you will focus on implementing geospatial analysis workflows to derive essential biodiversity variables from analysis-ready drone datasets. This postdoctoral role requires experience with and initiative in geospatial data science, machine-learning algorithm design, artificial intelligence (AI), and automation of workflows, ensuring that the NatureScan project delivers robust, reproducible products to stakeholders and end-users. The role requires a skilled geospatial scientist with experience in analysis of high-resolution drone data and Proficiency using programming languages (e.g., R or Python) for image analysis.

What you’ll do:

• Construct end-to-end geospatial workflows from image ingestion to generation of spatial and spectral derivates to feature detection.
• Design, train and validate advanced AI approaches (e.g. convolutional neural networks, ensemble classifiers) to quantify physiological and structural plant traits and essential biodiversity variables (EBVs).
• Integrate field-collected samples and AI/ML (cross-)validation techniques to rigorously assess model accuracy, producing formal error budgets and confidence maps.
• Package outputs into cloud-native geospatial formats and deliver to preferred web data platforms, such as the TERN data portal, accompanied by user guides and metadata documentation.
• Lead preparation of peer-reviewed publications and conference presentations that showcase methodological innovations and project findings.­

What we’re looking for:

• Demonstrated experience in processing drone-derived imagery and lidar data using industry-standard software and programming environments.
• Proficiency in Python or R for geospatial data processing, with experience in relevant spatial/AI/ML libraries. Demonstrated experience in implementation of AI/ML workflows for feature detection and generation of remote sensing products, including robust approaches to training, hyperparameter tuning, and performance assessment.
• Demonstrated knowledge of landscape ecology and/or plant physiology in the context of remote sensing applications.
• Strong understanding of data lifecycle management, version control, and metadata standards for geospatial datasets.
• Experience documenting technical procedures and collaborating with data service teams or similar technical support groups.

Salary details

Appointment to this role will be at Academic Level A and will have a total remuneration package of up to $125,877 comprising base salary within the range of $83,198 to $107,587 plus 17% superannuation.

How to Apply

• This vacancy is being advertised internally only in the first instance to current staff.
• In submitting your application, you acknowledge you have/intend to discuss your interest in this vacancy with your current manager and understand they may need to be contacted confidentially by the hiring manager as part of the assessment of your application.
• To apply online, please provide your CV and 1-2-page cover letter outlining your interest in the role, skills, capabilities and experience.  You do not need to separately address the success criteria.
• For further information about this position, please contact Arko Lucieer, Head of School of Geography, Planning and Spatial Sciences, Arko.Lucieer@utas.edu.au
• Please visit https://www.utas.edu.au/jobs/applying for our guide to applying and details on the recruitment process.
• Please refer to the attached Position Description Below for full details.

 Position Description - 501309 - Research Fellow in Drone Data Analytics.pdf

Applications close Wednesday, 20 August 2025, 11.55pm

As part of our commitment to a safe and inclusive workplace, employment history and police checks may be conducted as part of the selection process.

To be eligible for this position, you are required to hold Australian or New Zealand Citizenship, permanent residency or a valid visa that enables you to fulfil the requirements of this role.