Study with us

Image credit: The University of Queensland

Our Centre’s objective is to enable Australian organisations to achieve responsible, secure, and agile value creation from data. We will build workforce capacity in Data Science, Machine Learning and Artificial Intelligence.

As a HDR student with CIRES, you will have the opportunity to work collaboratively with university and industry partner supervisors on research with real world impact. During your degree, you will undertake a 12 month industry placement with the industry partner.

 

We offer a generous scholarship package and will be recruiting for projects throughout 2022.

We currently have three PhD positions advertised below, applications close on the 19th June 2022.

 

PhD Scholarship: Data as a Service Architecture

This is an opportunity for a highly motivated student to join the CIRES project team, collaborating closely with leading experts in the Queensland Police Service (QPS) to develop a prototype system to showcase the scalability, reliability, and usability of an AI-based data discovery system. This scholarship is one of three CIRES projects with QPS related to the responsible use of sensitive data assets.

For this project, CIRES is seeking a candidate with interdisciplinary interests and capabilities. The candidate will have qualifications relevant to this project, e.g., Master of Data Science, Computer Science, IT, and/or Bachelor of Computer Science, IT, Mathematics.

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.

 

Applications are now open and close on the 19th June 2022.

PhD Scholarship: Expanding Data Sets to Allow Improved Critical Care for Children – Inpatient Risk Prediction

This is an opportunity for a highly motivated student to join the CIRES project team, collaborating closely with leading experts in Queensland Health on investigating algorithm use and organizational implications in inpatient settings. This scholarship is one of three CIRES projects with Queensland Health related to paediatric sepsis management. The successful candidate will collaborate with Queensland Health to develop a platform-independent decision support framework using an interpretable machine learning approach to make effective risk predictions for paediatric patients at risk of sepsis.

This project seeks to develop a strong and capable future leader who can undertake medical analysis in a data-rich environment. The developed model will demonstrate the flexibility to be adapted and applied to other medical predictive tasks, e.g., sepsis prediction/monitor, linking genomics with risk prediction, etc.

For this position, CIRES is seeking a candidate with an understanding of concepts from applied statistics/probability, numerical linear algebra, machine learning, algorithms and complexity. This project also requires proficiency in Python programming language, and machine learning software packages such as Pytorch. CIRES particularly encourages applicants with a medical background and relevant knowledge in the research domain.

 

Applications are now open and close on the 19th June 2022.

PhD Scholarship: Interpretable AI-Theory and Practice

The ARC Training Centre for Information Resilience (CIRES) invites highly motivated and committed candidates to apply for a fully funded PhD position focused 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.

The candidate is 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.

 

Applications are now open and close on the 19th June 2022.

PhD Scholarship: Curating Systems of Engagement

This project tackles the critical issue of how information from an organisation’s public systems of engagement can be captured, developed  and leveraged as information assets of value and will contribute to methodologies for improving enterprise information and knowledge management. Working with partner Astral Consulting, the research will investigate how organisations can leverage human & AI/ML approaches to curate and incorporate the uncontrolled data accumulating in an organisations systems of engagement into its formal systems of record. A system of record is the legal, auditable system that tracks records while a system of engagement is where end-users carry out their tasks, such as collaborate on and complete business processes.

This research will investigate how AI/ML can meet the demand of utilising the information within systems of engagement, including the full range of communication and collaboration technologies in use but currently outside of existing organisational control.

PhD candidates should have a background in Information Systems, or Enterprise Information Management with a computing science or similar technology background preferred, but not essential.  A strong interest in technology and the business value of advanced data analytics, AI and machine learning is an advantage.  Previous experience in business analysis, enterprise architecture and/or working with metadata, taxonomies and Information Architecture is beneficial, but not essential.

 

Applications will open from mid-2022.

To register your interest in this project or find out more, contact us via cires@uq.edu.au

PhD Scholarship: Community Attitude to Law Enforcement Data

This is an opportunity for a highly motivated student to join the CIRES project team, collaborating closely with leading experts in the Queensland Police Service (QPS) to develop qualitative and participatory research methods that can be used by data-driven organizations to understand and better communicate the impact of using human data to customers, users, and the public. This scholarship is one of three CIRES projects with QPS related to the responsible use of sensitive data assets.

For this project, CIRES is seeking a candidate with a background in Information Systems or Psychology, with a strong interest in technology business value and trust. Prior experience and knowledge in qualitative and design methodologies is preferred.

 

Applications will open from mid-2022.

To register your interest in this project or find out more, contact us via cires@uq.edu.au

PhD Scholarship: Customer Data Stories 

The ARC Training Centre for Information Resilience (CIRES) invites highly motivated and committed candidates to apply for a fully funded PhD position focused on how to improve data curation through a crowd-sourced approach. In line with CIRES’s industry engagement objectives, the position is defined and co-funded in close collaboration with Allianz Partnersthe world’s largest diversified insurance company. This scholarship is one of two CIRES projects with Allianz related to organisational and transformational aspects of data, algorithms, and AI.

The successful candidate is expected to have a good background in data science, data analytics, or machine learning and will develop novel data-driven marketing methods making research contributions over the entire Artificial Intelligence pipeline: from data collection and curation to model training and deployment with end users including evaluation.

This project seeks to develop a strong and capable future leader who can undertake data analysis in a data-sparse environment focussing on personalised marketing, with the proposed model and research tasks able to be adapted and applied to other human-in-the-loop tasks.

For this position, CIRES is seeking a candidate with an understanding of concepts from applied statistics/probability, machine learning, algorithms and complexity, human-computer interaction, and marketing. This project also requires proficiency in the Python programming language, and machine learning software packages such as Pytorch or Tensorflow.

 

Applications will open from mid-2022.

To register your interest in this project or find out more, contact us via cires@uq.edu.au

PhD Scholarship: Human-Centred Data Literacy Curriculum for Complex Educational Organisations

The ARC Training Centre for Information Resilience (CIRES) invites highly motivated and committed candidates to apply for a fully-funded PhD position focused on curriculum development for data literacy. The successful candidate will work in close collaboration with their advisory team, leading experts in the Queensland Department of Education (DoE) and school leaders and teachers to develop curriculum for a data literacy framework, design and undertake a field study for adaptive delivery of the curriculum, and evaluate the effectiveness of the developed curriculum and methods of adaptive delivery.

For this position, CIRES is seeking a candidate with interdisciplinary interest and capabilities. The ideal candidate will have a passion and experience in teaching and developing learning content (as a tutor or a teacher), experience with field or lab research using quantitative and qualitative methods as well as strong written and communication skills.

 

Applications will open from mid-2022.

To register your interest in this project or find out more, contact us via cires@uq.edu.au

PhD Scholarship: Expanding Data Sets to Allow Improved Critical Care for Children – Outpatient Risk Prediction

This is an opportunity for a highly motivated student to join the CIRES project team, collaborating closely with leading experts in Queensland Health on investigating machine learning techniques for designing risk predictive models in outpatient settings. This scholarship is one of three CIRES projects with Queensland Health related to paediatric sepsis management. The successful candidate will collaborate with Queensland Health to develop a probabilistic based risk prediction system that identifies the future clinical abnormalities of children at risk of infection and sepsis.

This project seeks to develop a strong and capable future leader who can undertake medical analysis in a data-sparse environment, with the proposed model and research tasks able to be adapted and applied to other medical predictive tasks.

For this position, CIRES is seeking a candidate with an understanding of concepts from applied statistics/probability, numerical linear algebra, machine learning, algorithms and complexity. This project also requires proficiency in Python programming language, and machine learning software packages such as Pytorch. CIRES particularly encourages applicants with a medical background and relevant knowledge in the research domain.

 

Applications will open from mid-2022.

To register your interest in this project or find out more, contact us via cires@uq.edu.au

PhD Scholarship: Developing Analytics-Driven Organisations

The ARC Training Centre for Information Resilience (CIRES) invites highly motivated and committed candidates to apply for a fully funded PhD position focused on how data analytics can drive organizational transformation. In line with CIRES’s industry engagement objectives, the position is defined and co-funded in close collaboration with Aginic, an emerging leader in the field of analytics that employs agile and user-centric approaches to build their competitive solutions. This scholarship is one of two CIRES projects with Aginic related to organisational and transformational aspects of data, algorithms, and AI.

The successful candidate will become part of Aginic’s multidisciplinary analytics teams, or squads, and will collaborate and participate in industry-led analytics projects, as part of the process of conducting engaged research. This project will develop a systematic and organized approach to data-driven transformations and will help Aginic and other companies progress data-driven transformation journeys.

For this position, CIRES is seeking a candidate with interdisciplinary interest and capabilities. The candidate will need knowledge in at least one of three areas: (i) business management or management information systems, (ii) computer science or data analytics, and (iii) economics. We do not expect candidates to have knowledge/expertise in all three areas, but combinations of expertise will be highly useful and desirable. Experience with field research and qualitative methods will also be valuable.

 

Applications have now closed.

PhD Scholarship: Bias Mitigation in Human in the Loop Decision Systems

This is an opportunity for a highly motivated student to join the CIRES project team, collaborating closely with leading experts in the Queensland Police Service (QPS) to generate more transparent, fair, and trustworthy decision-support systems driven by data and controlled by humans. This scholarship is one of three CIRES projects with QPS related to the responsible use of sensitive data assets.

The successful candidate is expected to have a good background in data science, data analytics, or machine learning and will develop novel bias tracking, management, and reduction method over the entire Artificial Intelligence pipeline: from data collection and curation to model training and deployment with end users.

This project seeks to develop a strong and capable future leader who can undertake data analysis in a data-sparse environment, with the proposed model and research tasks able to be adapted and applied to other human-in-the-loop tasks.

For this position, CIRES is seeking a candidate with an understanding of concepts from applied statistics/probability, machine learning, algorithms and complexity, and human-computer interaction. This project also requires proficiency in the Python programming language, and machine learning software packages such as Pytorch or Tensorflow.

 

Applications have now closed.