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Automated Penetration Testing using Improve Deep Reinforcement Learning Techniques

Automated Penetration Testing using Improve Deep Reinforcement Learning Techniques

Australia 16 Jan 2023
The university of Queensland Australia

The university of Queensland Australia

State University, Browse similar opportunities

OPPORTUNITY DETAILS

State University
Area
Host Country
Deadline
16 Jan 2023
Study level
Opportunity type
Opportunity funding
Full funding
Eligible Countries
This opportunity is destined for all countries
Eligible Region
All Regions
Enrolment status: Future UQ student
Student type: Domestic, International
Study level: Postgraduate research (HDR)
Study level: Computer science and IT
Scholarship focus: Academic excellence
Funding type: Living stipend, Tuition fees
Scholarship value: $32,192 per annum (2023 rate), indexed annually
Scholarship duration: 3.5 years with the possibility of 1 extension in line with UQ and RTP Scholarship Policy
Number awarded: May vary
Applications open: 23 December 2022

Eligibility:

You're eligible if you meet the entry requirements for a higher degree by research.

Selection criteria:

Your application will be assessed on a competitive basis.

We take into account your:

  • previous academic record
  • publication record
  • honours and awards
  • employment history

A working knowledge of computer science and cybersecurity would be of benefit to someone working on this project.

You will demonstrate academic achievement in the field/s of cybersecurity and the potential for scholastic success.

A background or knowledge of computer science, cybersecurity, and pen testing is highly desirable.

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