PhD Scholarship in Computer Vision & Machine Learning, 2021 is offered for PhD degree in the field of Engineering and Computing. You can apply to this scholarship here. The deadline for the sending your application is 07 Mar 2021. This scholarship is provided by University of Queensland (UQ) and the value of this scholarship is Partial Funding, $28,597 per annum . This scholarship is open for: Open to all nationals.

• Degree: PhD
• Provided by: University of Queensland (UQ)

• Deadline: 07 Mar 2021
• Scholarship value: Partial Funding, $28,597 per annum

University of Queensland (UQ) has initiated PhD Scholarship in Computer Vision & Machine Learning to all students enrolling in PhD course of study at the university. The project is supported by the Australian Research Council and involves academic partners in both Europe and the US.

Value of the PhD Scholarship in Computer Vision & Machine Learning, 2021:

Successful applicants of the PhD Scholarship in Computer Vision & Machine Learning, 2021 will receive al iving stipend scholarship of value $28,597 per annum (2021 rate), indexed annually.

• Applicants from all nationalities are eligible.
• Applicants must have completed some research experience.
• Applicants must have very good first Masters or honours degree in mathematics, computer science or science.
• Applicants must have completed an approved university degree.
• Applicants must meet the English language requirements.

To be considered for this scholarship, please email the following documents to Associate Professor Anders Eriksson (a.eriksson@uq.edu.au) 

• Cover letter
• CV
• Academic transcript/s
• Evidence for meeting UQ's English language proficiency requirements eg TOEFL, IELTS

Please note the following: Submitting the above documents does not constitute a full application for admission into The University of Queensland's PhD program. If you are selected as the preferred applicant, you will then be invited to submit a full application for admission. You can familiarise yourself with the documents required for this process on the Future Student's website.