PhD Position -- Machine Learning (Airport Baggage Inspection)
A fully funded PhD position in Machine Learning is available at Flinders University, Adelaide, Australia. The project will focus on machine learning and deep learning approaches in processing, segmenting, identifying, and analyzing 3D x-ray CT images for automated baggage inspection at airports. The scholarship includes a stipend of $35,000 per annum and an industry internship of at least 60 full-time equivalent days.
Candidates with a related background in Image processing, image analysis, Computer Science, ICT and Engineering, Physics, Mathematics and Statistics are invited to apply. Demonstrated working knowledge of Machine Learning with images and good programming skills in python is essential. Knowledge of CT scan and other programming languages such as MATLAB 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.
Application Information:
To apply, please send an expression of interest (EOI) to Dr Gobert Lee gobert.lee@flinders.edu.au with “EOI PhD Scholarship” in the Subject field of the email. The EOI should 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/professional referees.
Application deadline is for a guide only. The position may be filled earlier. EOI will be reviewed on a rolling basis. Shortlisted candidates will be invited to submit a full application.
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