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CIRES PhD Scholarship: Interpretable AI - Theory and Practice

Enrolment status
Future UQ student
Student type
Domestic, International
Study level
Postgraduate research (HDR)
Study area
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
20 April 2022
Applications close
19 June 2022

About this scholarship

Supervisor: Dr Fred Roosta-Khorasani

This PhD project focuses on researching interpretable machine learning algorithms to understand how black-box models behave and provide theoretical foundations for algorithmic safety. In line with CIRES’s industry engagement objectives, the position is defined and co-funded in close partnership with the highly successful Brisbane-based consultancy – Max Kelsen. In collaboration with Max Kelsen Partner Investigator Dr Maciej Trzaskowski, an expert in machine learning and quantum computing, the candidate will develop applications for health and genomics data analysis using the data repositories held by Max Kelsen.

Max Kelsen has active research, development, and consulting activities in the fields of AI and cancer genomics and has prioritized AI safety as a key ingredient of any new product prior to deployment. This scholarship is one of two CIRES projects with Max Kelsen related to organisational and transformational aspects of data, algorithms, and AI.

Research environment

The Australian Research Council (ARC) Industrial Transformation Training Centre for Information Resilience (CIRES) is a partnership with the University of Queensland, Swinburne University of Technology, and partner organisations from Industry and Government. Our objective is to enable Australian organisations to achieve responsible, secure, and agile value creation from data, while building workforce capacity in Data Science, Machine Learning, and Artificial Intelligence.

Our PhD positions are part of an innovative Higher Degree by Research (HDR) training program provided by CIRES. You will have the opportunity to work collaboratively with university and industry partner supervisors who are leading research with real world impact. Their research will build on strong foundations of responsible data management, focusing on curating data at scale and building trusted data relationships to lift the socio-technical berries to data driven transformation.

During your degree, you will undertake a one-year (equivalent) placement with the industry or government partner. We offer a generous scholarship package of $34,938 per annum (indexed annually) and top-up scholarship from $5,000 per annum.

Positions are based at the University of Queensland St Lucia Campus, in Brisbane, Australia. We invite highly motivated and committed candidates to apply for these fully funded PhD positions. For more information visit the CIRES website or contact us via cires@uq.edu.au

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 4, 2022 (October commencement), or Research Quarter 1, 2023 (January commencement).

How to apply

Before submitting an application you should:

You apply for this scholarship when you submit an application for a Doctor of Philosophy (PhD). You don't need to submit a separate scholarship application.

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 ‘AI-ROOSTA-KHORASANI’ in the 'Name of scholarship' field.

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

You are expected to have good understanding of concepts from applied statistics/probability, numerical linear algebra, and machine learning. Proficiency in Python programming language and machine learning software packages such as Pytorch is required.

Rules

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.

Contact

Dr Fred Roosta-Khorasani