Machine Learning in Computer Vison (Airport Baggage Inspection) – PhD scholarship
College of Science and Engineering
$35,000 per annum
3 years (6 month extension possible)
Level of Study
Higher Degrees Research
**Please note the closing date is a guide only. This opportunity may close earlier if the position is filled.
A full-time PhD scholarship is available in the area of Artificial Intelligence / Machine Learning in Computer Vision for students pursuing a PhD study. The project will develop machine learning and deep learning approaches in processing, segmenting, identifying, and analyzing 2D and 3D x-ray images for automated baggage inspection at airports. The scholarship includes an industry internship of at least 60 full-time equivalent days.
Candidates with a related background in Computer vision, Image processing and image analysis, Computer Science, ICT and Engineering, Physics, Mathematics and Statistics are invited to apply. Demonstrated working knowledge of Computer Vision and Machine Learning in images is essential. Good programming skills in python is essential. Knowledge of CT scan is beneficial. Ideally, the successful candidate should have journal publications and/or conference presentation experience.
The successful candidate will work under the supervision of Dr Gobert Lee https://www.flinders.edu.au/people/gobert.lee and Dr Mariusz Bajger and will collaborate with academic and industrial collaborators. We are looking for a highly self-motivated student. The successful candidate must be able to work independently as well as a member of a team. The successful candidate must demonstrate excellent oral and written communication skills as well as interpersonal skills towards staff, students, and collaborators.
Interested candidates MUST first send expression of interest (EOI) to Dr Gobert Lee firstname.lastname@example.org. Please state “EOI PhD Scholarship” in the subject of the email and please include
(1) a cover letter outlining your research interests, your motivation for pursing a PhD, and your suitability for this project;
(2) a curriculum vitae (including education, work/research experience and publications);
(3) academic transcripts; and
(4) contact details of two academic/industry referees.
Please note that the closing date is a guide only. This opportunity may close earlier if the position is filled. EOI will be accepted and reviewed on a rolling basis. Shortlisted candidates will be invited to submit a full application.