PhD in Automated Detection of Archaeological Features Using Drone Imaging and AI Flinders University in Australia

This PhD project at Flinders University aims to develop and test innovative methods for automatically detecting archaeological features using drone-based photography and artificial intelligence. The research will focus on the vast desert landscapes of Australia, collaborating with industry partners to explore how high-resolution aerial imagery can be analysed using computer vision and machine learning. The primary target is the detection of stone artefact scatters, which are widespread and informative forms of archaeological evidence in arid Australia. The project will also investigate the automatic identification of other archaeological landscape features visible in aerial imagery.

Australia’s desert regions contain extensive archaeological records but are challenging to survey using traditional ground-based methods. By developing automated detection approaches, this project aims to significantly increase the scale and efficiency of archaeological survey. The research has the potential to transform how archaeological landscapes are identified and monitored, support improved cultural heritage management, assist Indigenous communities in protecting cultural sites, and enable a more effective archaeological assessment framework for industry and land disturbance activities.

Through testing multiple automated detection approaches, including advanced computer vision and machine learning techniques, the project will help establish new digital methods for large-scale archaeological survey in arid environments. This opportunity is ideal for students interested in combining archaeology, artificial intelligence, drone technology, and digital survey methods to address real-world challenges in cultural heritage management and landscape assessment.

Applicants are encouraged to apply online via the Flinders University scholarship portal. Please review the university website for further details and application instructions.