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CIRES-Queensland Police Service (QPS) PhD Scholarship

CIRES-Queensland Police Service (QPS) PhD Scholarship

Australia 06 Oct 2022
The university of Queensland Australia

The university of Queensland Australia

State University, Browse similar opportunities

OPPORTUNITY DETAILS

State University
Area
Host Country
Deadline
06 Oct 2022
Study level
Opportunity type
Specialities
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: Arts, humanities and social sciences, Business and economics, Computer science and IT, Education, Engineering, Health and medicine, Science and mathematics
Scholarship focus: Academic excellence
Funding type: Living stipend, Top-up, Tuition fees
Scholarship value: $34,938 per annum (2022 rate), indexed annually. A top-up of $5,000 per annum is also available.
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: 25 August 2022

Eligibility:

To be eligible to apply, you must:

  • Meet the entry requirements for Higher Degrees by Research at UQ
  • Be nominated by the Principal Advisor and enrolling school or institute at UQ
  • Submit a 2-page overview with your application addressing:
    • Why you are interested in this project
    • What challenges you foresee in the project
    • What special insights or capabilities you would bring to the project
    • How you see the project and PhD as part of your career trajectory
  • Complete an interview process with the UQ supervisory team and industry or government partner

Applicants for this scholarship should be aiming to commence in Research Quarter 1, 2023 (January commencement), or Research Quarter 2, 2023 (April commencement).

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

The candidate will have a good background in data science, data analytics, or machine learning, preferably with expertise in predictive analytics, graph mining, and causal inference.

Experience working with and mining structured and unstructured data from multiple sources is also desirable. 

Proficiency in Python programming language and machine learning software packages such as Tensorflow and Pytorch is required.

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