PhD Scholarship in Satellite-Based Methane Detection

About the Role 
Are you passionate about cutting-edge research that makes a real-world impact? Swinburne University’s Space Technology and Industry Institute, in collaboration with CSIRO and Esper Industries, is offering an exciting PhD scholarship to tackle one of the most pressing environmental challenges—detecting methane emissions from space using advanced neural network technology.

This unique opportunity is part of CSIRO’s prestigious Industry PhD (iPhD) Program, designed to bridge the gap between academia and industry by developing innovative solutions for real-world challenges. As a PhD candidate, you will play a key role in advancing satellite-based methane detection, helping to improve the way Australia monitors and mitigates emissions. Your research will focus on developing AI-driven methods to analyse satellite imagery, identifying methane plumes with greater accuracy and efficiency than ever before.

With access to world-class expertise and cutting-edge facilities, you will work at the intersection of space technology, environmental science, and artificial intelligence. Your primary base will be at Swinburne University in Melbourne, with additional industry engagement at Esper Industries and potential collaboration with CSIRO’s Aspendale research facility.

If you are an Australian citizen, permanent resident, or New Zealand citizen looking to make a lasting impact in the field of climate science and AI-driven remote sensing, this is your chance to contribute to meaningful, high-impact research while gaining invaluable industry experience. 


About You  
To be suitable for this role you will need to have experience in the below key accountabilities: 

• Experience with training and implementing neural networks and/or analysing satellite imagery
• Experience working with large databases and/or developing image processing pipelines
• Strong programming skills
• Ability to work independently and collaboratively as part of a team 
• Strong communication skills, an ability to write high-quality technical reports and contribute to peer-reviewed academic publications

Qualifications
Completed undergraduate degree in physics, computer science, machine learning, computational modelling, or similar.


About Swinburne University of Technology 
Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and different university – one that is truly of Technology, of Innovation and of Entrepreneurship. We are committed to a differentiated university proposition in education and research. 


To Apply 
Please submit your CV and cover letter addressing your suitability for this position.  

To review the Position Description and to apply, please scroll down to the bottom of the page. 

If you are viewing this advert from an external site, please click ‘apply’ and you will be redirected to Swinburne’s Jobs website to access the Position Description at the bottom of the page.

Please Note: Appointment to this position is subject to passing a Working with Children Check.

If you are experiencing technical difficulties with your application, please contact the Swinburne Talent Acquisition Team on talentacquisition@swin.edu.au 


Applications Close: Sunday 13 April 2025, at 11.00pm


Diversity, Equity and Inclusion
Swinburne has become a world-class university, driving social and economic impacts through science, technology, and innovation. As a dual-sector university, our vision is for people and technology working together to build a better world.

Central to our vision is our commitment to diversity, equity, and inclusion. We pride ourselves on being an equal opportunity employer focused on attracting, retaining, and developing great talent. We work to remove barriers related to gender identity, culture, ethnicity, sexual orientation, disability, and age.

We strongly encourage applicants from diverse Aboriginal and Torres Strait Islander communities. Our Moondani Toombadool Centre leads our Indigenous education and culture at Swinburne, guided by community wisdom and leadership.

We support applicants with disabilities. Adjustments can be requested at any time during the recruitment process. For Reasonable Adjustment requests, including accessible formats for the PD, application form or any other document, please contact DCR@swin.edu.au or call +61 3 9214 3550.

Please note the above number and DCR email address are for disability or reasonable adjustments queries only. General enquiries about the role can be sent to talentacquisition@swin.edu.au (general enquiries will not be answered by phone).
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