PhD scholarship: From Synthetic to Real - Domain Adaptation for Data Augmentation

Summary

Enrolment status New students
Student type Domestic students, International students
Level of study Higher Degree by Research
Study area Engineering and Computing, Science and Mathematics
HDR funding type Living stipend scholarship
Scholarship value $28,092 per annum tax-free (2020 rate), indexed annually
Scholarship duration Three years with the possibility of two 6-month extensions in approved circumstances.
Opening date 13 February 2020
Closing date 10 March 2020

Description

This project aims to investigate the domain shift between synthetic and real data and develop advanced deep-learning models to address the open-set problem in domain adaption, which will be beneficial to a variety of real-world applications such as self-driving cars, cyber-security, etc.

Eligibility

To be eligible, you must meet the entry requirements for a higher degree by research.

Applications are closed.

Before you get started

If this scholarship has rules, download and read them.

How to apply

To apply for admission and scholarship, follow the link on the upper right of this page. There is no separate application for scholarship because you will have the opportunity to request scholarship consideration on the application for admission.

Before submitting an application you should:

When you apply, please ensure that under the scholarships and collaborative study section you:

  1. Select ‘My higher degree is not collaborative’
  2. Select 'I am applying for, or have been awarded a scholarship or sponsorship'.
  3. Select ‘Other’, then ‘Research Project Scholarship’ and type in ‘DOMAIN ADAPTATIONin the 'Name of scholarship' field.

See an example of what you have to do

Learn more about applying for a higher degree by research at UQ

Selection criteria

  1. Having a Master or Honour Degree in Computer Science, Data Science or Mathematics in Australia; or having Bachelor Degree obtained from other countries in equivalent academic areas.
  2. Having the research background in Computer Vision, Multimedia Retrieval, and Machine Learning. At least one CORE A*-ranked conference paper published in beforementioned areas is required.
  3. Being good at programming with deep learning packages, e.g., Tensorflow, Pytorch, etc.
Applications are closed.

Contact

Associate Professor Helen Huang
Applications are closed.

Terms and conditions

Read the policy on UQ Research Scholarships.

A domestic part-time student with carer’s responsibilities, a medical condition or a disability, which prevents them from studying full time may be eligible for scholarship consideration, on a case by case basis.

Applications are closed.