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Adaptable Machine Learning techniques for dynamic aerial scene understanding


National Centre for Geocomputation

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Dr T McCarthy No more applications being accepted Funded PhD Project (Students Worldwide)

About the Project

Funded by Science Foundation Ireland and involving collaboration with Industry partners including Airbus, Irelandia Aviation and Intel, U-Flyte is a R&D partnership, established to tackle the current global logjam impeding the wider development of drone operation and rollout of commercial services. The research work-plan is based around a series of inter-connected work-packages that deal with the development of novel airspace modelling tools and drone traffic management systems – also known as U-Space and Unmanned Traffic Management (UTM) systems. Advanced flight-testing is carried out at Waterford Airport and selected mobile locations across Ireland. Drone services including mapping, monitoring and logistics. Specialist aerial support services will also be developed and tested using real-world, end-use case scenarios. U-Flyte comprises Geospatial Scientists, Software Engineers, Mathematicians, Domain Specialists and Drone Operations personnel, working with the latest Vertical Take-off and Landing (VTOL) and hybrid drones, sensors (Optical, LiDAR, Navigation, Radar) and cloud computing resources. At the heart of U-Flyte is advanced computational expertise including autonomous navigation, Machine Learning and Geospatial Analytics all dedicated to developing the next generation of Beyond Visual Line of Sight (BVLOS) autonomous drone services.

U-Flyte now wishes to recruit PhD candidates to join this aerial robotics team based within the National Centre for Geocomputation (NCG), an established research centre at Maynooth University. We would especially like to hear from candidates with good primary degrees in Computing or Mathematics interested in developing careers in Aerial Robotics, Machine Learning, Computer Vision & Geospatial Data Analytics. If you feel you have the right background and want to know more – please get in touch.

Drones are capable of flying for more than an hour, covering tens of kilometres in distance, recording GigaBytes of combined optical and navigation data. Automated classification and measurement of man-made and natural features will become an increasingly important role for data-gathering drones. This PhD will investigate novel Machine learning (ML) tools and methodologies for identifying objects and activities in real-world scenes. These new ML tools will be tested and assessed for a variety of mapping, monitoring, defect inspection and anomaly detection tasks

Application Procedure:

Please contact Dr. Lucy Cradden, U-Flyte Project Manager at [Email Address Removed] to discuss further


Funding Notes

U-Flyte Doctoral Scholars will receive an annual (tax-free) stipend of €18,000 (paid monthly) and tuition fees over the 4 year PhD duration, will be paid at the EU rate, directly by the project.
Scholars will have a dedicated work-space/I.T. within the NCG’s postgraduate area and join an experienced team operating in an innovative, dynamic environment.
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