Organisation/Company The University of Adelaide Research Field Computer science » Modelling tools Geosciences » Other Computer science » Systems design Computer science » Programming Computer science » Informatics Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Sep 2026 - 17:00 (Australia/Adelaide) Country Australia Type of Contract Not Applicable Job Status Full time Hours Per Week 38 Offer Starting Date 1 Feb 2027 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No
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Offer Description
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Wildfires cause severe loss of life, property and ecosystems, making rapid detection vital. Small satellites can now use onboard AI to detect fires and transmit alerts rather than imagery, as demonstrated by our team on different SmallSat missions.
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This PhD will address two key limitations: limited labelled training data and the isolated analysis of individual satellite passes. It will investigate Earth-observation foundation models to improve fire detection from limited training data and develop lightweight models for onboard deployment. It will also explore agentic AI and constellation-scale approaches to combine repeated observations across Australian-led satellite constellations,
helping confirm fire progression, reduce false alarms and prioritise urgent alerts. The research will advance Adelaide University's SmartSat CRC-funded work towards operational early wildfire detection.
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Wildfires cause severe loss of life, property and ecosystems, making rapid detection vital. Small satellites can now use onboard AI to detect fires and transmit alerts rather than imagery, as demonstrated by our team on different SmallSat missions.
n
Wildfires cause severe loss of life, property and ecosystems, making rapid detection vital. Small satellites can now use onboard AI to detect fires and transmit alerts rather than imagery, as demonstrated by our team on different SmallSat missions. This PhD will address two key limitations: limited labelled training data and the isolated analysis of individual satellite passes. It will investigate Earth-observation foundation models to improve fire detection from limited training data and develop lightweight models for onboard deployment. It will also explore agentic AI and constellation-scale approaches to combine repeated observations across Australian-led satellite constellations, helping confirm fire progression, reduce false alarms and prioritise urgent alerts. The research will advance Adelaide University's SmartSat CRC-funded work towards operational early wildfire detection.
📌 Full PhD scholarship available at Adelaide University, South Australia: SRConstellation-Scal
🏢 The University of Adelaide
📍 South Australia
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