PhD Fellowship, Information Architecture and Forensic Data Analytics Work with SWINBURNE UNIVERSITY OF TECHNOLOGY

  • Become a leader in emerging digital technologies
  • Placement with a leading industrial partner
  • $33,413 per year for up to 3.5 years (full-time, term)

This is an opportunity to undertake your PhD in an innovative HDR training program with the Australian Research Council (ARC) Center for Industrial Transformation Training for Information Resilience (CIRES) .


The Center for Information Resilience (CIRES) is an industrial transformation training center of the Australian Research Council (ARC), established in partnership with Swinburne University of Technology and the University of Queensland.

The Center aims to build workforce capabilities in Australian organizations to create, protect and maintain agile data pipelines, capable of detecting and responding to failures and risks throughout the data value chain. information in which data is extracted, shared, transformed, analyzed and consumed. Further information on CIRES is available at

About Swinburne University of Technology

Swinburne is a multi-sector science, technology and innovation university with over 54,000 students and 5,000 staff worldwide. We offer postgraduate, undergraduate, professional and online education to provide students with a variety of work-relevant pathways. Our mission is to be a world-class university, creating economic and social impact through science, technology and innovation. Our goal is to provide future-ready learners, impactful research and innovative enterprise.

About this scholarship

This project will develop an automated horizon scanning tool (AHS) based on patents, academic literature and gray literature to address the time and resource cost issues associated with traditional horizon scanning. The AHS tool will support the strategic positioning of companies and research groups by enabling insight into the landscape of pre-existing technologies relevant to their proposed innovations. The AHS will also provide insight into areas where gaps exist in the current technology landscape, thereby identifying promising future areas of research or potential funding. The development of AHS will require the implementation of natural language processing and machine learning algorithms to identify patents and search documents that are semantically similar to a given query document, as well as topic modeling to identify technological gaps.

Once fully developed, the AHS will allow users to continuously monitor the existing technology landscape in an interactive and visually intuitive environment. This will require the tool to be developed in a cloud environment and include interactive dashboards and intuitive data visualizations. The AHS will also enable rapid literature searches for researchers, and identifying technology gaps using the AHS will inform future search strategies and the scope of potential research projects.

This PhD scholarship is based at Swinburne University of Technology, Melbourne. This may also involve travel to meet the CIRES partner at the University of Queensland in Brisbane.

Candidate background

It is beneficial, but not essential, that applicants have:

  • A background in information systems or business information management with a background in computer science or similar technology
  • A keen interest in technology and the business value of advanced data analytics, AI and machine learning
  • Understanding of graph modeling or named entity recognition

Essential eligibility criteria

  • Fulfill the entry requirements for higher degrees by research at Swinburne University of Technology
  • Understanding of natural language processing and data mining
  • Experience working with big data and large scale databases
  • Demonstrated strong social and adaptive communication skills to interact with a range of people from the community, industry and academia
  • Excellent project management and attention to detail
  • Ability to work both independently and as part of a team in a collaborative manner
  • Enthusiasm for learning new research and data analysis skills and systems
  • Ability to contribute to peer-reviewed academic publications
  • Is an Australian citizen and must undergo a pre-engagement check
  • Must be able to enroll and commence PhD candidacy by end of June 2022.

A full list of selection criteria is available in the job description.

Terms and conditions

The scholarship will be governed by the Terms and Conditions of the Swinburne Research Scholarship.

All appointments are subject to a valid Working with Children’s Check; it is mandatory to have and maintain an up-to-date child labor check.

How to apply and more information

For see job description or to start an application please click apply or “begin” and send a CV, cover letter and answer to the key selection criteriaas indicated in the job description.

Any specific scholarship inquiries can be directed to Professor A/Amir Aryani (CIRES) at [email protected]

If you are having technical difficulties with your application, please contact the recruitment team on [email protected]

Help and support

We are committed to making the recruitment process fair and equitable for all of our applicants. If you have specific accessibility or support needs, please contact Maree Norden, Diversity and Inclusion Manager at [email protected] For help or questions regarding Aboriginal and Torres Strait Islander employment, please contact Timothy Werner at [email protected]

Swinburne offers flexible work options, time off and parental/caregiver policies to support work-life balance.

Victoria’s Minister of Health orders require all workers at Swinburne to be fully vaccinated against COVID-19, unless they are an excepted person as defined by the Compulsory Vaccination Order 2021 COVID-19 pandemic (specified workers) (#1). All applicants must therefore be able to comply with this requirement..

Applications closed at 5 p.m. on Sunday, April 10, 2022.

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