PhD Scholarship in Deep Learning for Magnetic Resonance Imaging at School of Information Technology and Electrical Engineering

Applicants are invited to apply for a PhD position in computer science at The University of Queensland. Successful candidate will have funding to work and study for three years in Australia. The deadline for applying is January 02, 2019.

It is an exciting time to get involved with the School of Information Technology and Electrical Engineering (ITEE), located on UQ's St Lucia campus. The School is ramping up its investment in teaching, research and engagement to create an inspiring, diverse and flexible workplace. The direction is backed by a bold, new strategic vision to ensure the School is at the forefront of meaningful research outcomes and pedagogy across its core impact areas of health, data, automation and energy. Boasting strong student enrolments in professionally accredited programs, combined with world-class researchers and facilities, the School is focused on strengthening its position in the global computer science and engineering communities. By attracting the brightest minds and fostering a truly innovative and collaborative work environment, the School will develop global solutions to contemporary issues and mentor the leaders of tomorrow.

We are seeking a talented PhD candidate to work on image processing and machine learning algorithms applied to medical imaging data such as MRIs. The candidate will explore deep learning methods for image reconstruction, segmentation and synthesis of these types of data. This will have the potential to improve the automation of image analysis of MRIs that are usually mundane and laborious tasks for clinicians, freeing up more time for patient care. Outcomes of this project will include faster MRI imaging through parallel algorithms that could make MRI more affordable (see for example recent UQ News article). The project will also develop automatic segmentation schemes that could potentially be deployed commercially on MRI scanners, supporting clinicians to improve the health outcomes of their patients in the future.

This scholarship is open to Australian citizens and international applicants. Applicants should possess a degree in Electrical or Biomedical Engineering (or equivalent) from an Australian University or a Master's Degree with a high GPA from a reputed overseas University with specialisation in electrical or biomedical engineering. Prior experience in image processing and machine learning is preferred. The candidate should also have good general research skills, a strong methodological background, excellent analytical skills, very good writing ability and the capacity to work with industry engineers.

This scholarship is funded by the School of ITEE at the Australian Government's RTP rate of $27,596 per year (2019), tax-free for three years with the possibility of two 6-month extensions in approved circumstances.

This PhD position will start in RQ2 or RQ3 2019.

To discuss this role please contact Dr. Shekhar Chandra -

To submit an application for this role, please use theApplybutton below.It is mandatorythat all applicantsMUSTsupply the following documents:Cover letter, your detailedresumeandcomplete academic records(including GPA scores/grades, and grading scale details).


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