CIRES PhD, Job in knowledge exploration with SWINBURNE UNIVERSITY OF TECHNOLOGY

  • Doctoral Fellowship, Knowledge Extraction from Scientific Papers and Invention Patents
  • Full-time term position at our Hawthorn campus
  • Annual allowance of $34,635 (indexed annually)

About the role

This research is a unique opportunity to develop skills and experience in advanced artificial intelligence technologies and to work closely with IP Australia to better understand the latest scientific discoveries and innovations.

About the scholarship

This scholarship is offered by an innovative HDR training program with the Center for Information Resilience (CIRES). 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 across the data value chain. information in which data is extracted, shared, transformed, analyzed and consumed. . This research is funded in partnership with IP Australia, with the aim of creating a pathway for automated exploration of knowledge from scientific papers and invention patents.

Many pre-existing technologies can be identified through patent documents and academic research papers, a process sometimes referred to as “horizon scanning” or “technology landscape.” This project aims to develop a new AI-driven approach to technological landscaping based on patents and academics. The new approach will support the strategic positioning of companies and research groups by allowing insight into the landscape of pre-existing technologies relevant to their proposed innovations. This research will provide insight into where gaps exist in the current technology landscape, thereby identifying promising future areas of potential innovation. This project will involve the application of natural language processing and machine learning algorithms to identify patents and search papers semantically similar to a given query document, as well as topic modeling to identify technology gaps.

This PhD scholarship is based at Swinburne University of Technology, Melbourne, and will also include an internship with government partner organization IP Australia. This may also involve travel to meet the CIRES partner at the University of Queensland in Brisbane.

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

  • a background in data science, computer science, machine learning, or similar scientific and technological background
  • a keen interest in technology and the business value of advanced data analytics, AI and machine learning

Essential eligibility criteria

Please meet these selection criteria as part of your application.

  • 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 academic sectors
  • Ability to contribute to peer-reviewed academic publications
  • Must be able to enroll and commence PhD candidacy by the end of August 2022.

About Swinburne University of Technology

Swinburne Horizon 2025 builds on our understanding of future challenges. With this new strategic plan, we choose to make Swinburne the prototype of a new and different university – one that is truly technology, innovation and entrepreneurship driven, and proud of it. We are committed to a differentiated university offer in terms of teaching and research, so that:

  • Every Swinburne learner gains work experience
  • Every Swinburne graduate gets a job
  • Each Swinburne partner receives a technology solution
  • Swinburne is the prototype of global best practice

Achieving our 2025 moon shots depends on our ability to work collectively, always, like One Swinburne.

To apply

To view the job description or to begin an application, click “apply” or “get started” and submit a resume, cover letter, and answers to essential eligibility criteria as outlined in the job description.

For more information on this role and to view the job description; please click “apply” or click it at the bottom of the ad.

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

Any scholarship specific questions can be directed to A/Prof Amir Aryani (CIRES) at

Please note: Appointment to this position is subject to passing a child labor check.

If you are experiencing technical difficulties with your application, please contact Swinburne’s Talent Acquisition team at

Applications closed at 5:00 p.m. AEST on Thursday, June 30, 2022

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

Diversity and Inclusion

Swinburne is a large, culturally diverse organization and we pride ourselves on our commitment to equity and inclusion through key initiatives. For more information on all of our initiatives, visit our Equity and Diversity website

We welcome and encourage applicants from diverse backgrounds to apply.

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 Norden tideDiversity and Inclusion Manager at

Aboriginal and Torres Strait Islander

We welcome and strongly encourage applications from Aboriginal and Torres Strait Islander people.

For any support please contact our Indigenous Employment Coordinator at or for more information on our Indigenous Strategies please follow the link to our RAP Reconciliation Action Plan

Vaccination requirements

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.

We are a Circle Back 2022 employer – we are committed to responding to every candidate.

Donald E. Patel