Development of an occupant detection system for vehicle seating that detects the presence of the occupant and the wearing of the seatbelt. The design will include wireless transmission to a main display unit that will record/store/transmit the data to a head office.

This project will use AI and ML to extract and map farm based assets, such as troughs, silos, tanks, water bodies and fences from high resolution RGB imagery and LiDAR point cloud data, replacing the need for manual digitisation of such assets. This is a cutting-edge project applying AI and ML to push the boundaries as far as possible.

“WaveSense” combines AI and mmWave signal processing to redefine human presence detection. This project delivers precise real-time sensing with application in smart environments and beyond. Candidates will engage with state-of-the-art mmWave tech, gain hands-on experience in AI-driven signal processing, contribute to impactful real-world innovations.

Join Quickstep’s eVTOL UAS development team, where you’ll develop advanced control systems, conduct cutting-edge simulations, and validate innovative aerospace technology, driving the future of advanced air mobility.

Scaling of monocular photogrammetry using acoustics is of high value to a number of fields including defence, commercial and environmental. This technology would allow high cost reduction on the acquisition of this kind of data.

All PhD and Masters by Research students are encouraged to submit an expression of interest to join the APR.Intern database. These submissions are viewed by industry partners with the intention of creating internship projects.