- Based in UniSA Education Futures at the City West campus
- Full-time, 3-year fixed term contract
- Salary Band: $112,892 - $133,388 per annum (plus 17% superannuation)
About the Role
The role of the Postdoctoral Research Fellow in Data Science is to conduct analyses on student engagement and learning within virtual environments and develop data-driven solutions that inform and lead to improved student engagement or learning outcomes using artificial intelligence, learning analytics, and learning engineering. In collaboration with staff from the Centre for Change and Complexity in Learning (C3L), staff at the University of Pennsylvania, staff at the University of Minnesota, and project partners who are taking part in the Learning Engineering Virtual Institute (LEVI) Consortium, the role will analyse data collected by LEVI project teams and provide the teams with analyses relevant to their goals of improving student engagement and learning, to facilitate student success outcomes. In addition, the role will undertake high-level applied research to reveal new insights into student engagement and learning and ways to optimise and improve online learning practices.
About UniSA
The University of South Australia is Australia’s University of Enterprise. Our culture of innovation is anchored around global and national links to academic, research and industry partners. Our graduates are the new urban professionals, global citizens at ease with the world and ready to create and respond to change. Our research is inventive and adventurous and we create new knowledge that is central to global economic and social prosperity.
Core Responsibilities
- Develop novel artificial intelligence and learning analytics methods to identify underlying patterns and associations with student engagement and learning outcomes
- Use data to derive insights that can be used to improve student engagement and learning outcomes
- Participate in learning engineering initiatives
- Use novel artificial intelligence and learning analytics methods to derive automated models that can be embedded into learning engineering interventions
- Collaborate with external industry stakeholders within the LEVI Consortium to provide automated models to them and support in integrating the models into their systems
Essential Skills and Experience
- A PhD qualification in a relevant discipline (e.g. artificial intelligence, data science, statistics, computer science, learning engineering, learning analytics or educational data mining) and experience in analysing and reporting on student learning data
- Demonstrated knowledge of education theory and quantitative and qualitative educational research methodologies
- Experience with natural language processing and automated text analysis
- Demonstrated experience in learning analytics, educational data mining and artificial intelligence in education, with the ability to use technical skills to find solutions to unidentified problems
- Experience using cloud-based infrastructure (e.g., Microsoft Azure or AWS) and Python and/or R programming languages to analyse educational data
Benefits
Getting a great job working with the best is just the start. UniSA rewards its staff with a wide variety of benefits such as:
- Access to great personal development opportunities
- Generous superannuation contributions of 17%
- Corporate health insurance
- Staff study support
- A variety of leave arrangements
Culture
At the University of South Australia, we value workplace diversity and are committed to providing a supportive, inclusive, and respectful work environment for all people. We strongly encourage applications from Aboriginal and Torres Strait Islander Peoples, women, members of the LGBTIQ+ community, people of culturally diverse backgrounds and people with disability.
Start Your Unstoppable Career!
For a copy of the position description and to apply, please visit Working at UniSA. The online application form will list the specific selection criteria that you need to address.
Please address your cover letter to Kendelle Newby, Consultant: Recruitment Central. For further information about the position or the recruitment process, please contact UniSA Recruitment Central on +61 8 8302 1700 or via email at recruitment@unisa.edu.au using job reference number 7078.
Applications close: 11:30pm Sunday 30 March 2025
We are committed to providing an equitable and barrier free recruitment process and encourage you to share any support, adjustments and/or access requirements you have by contacting our Recruitment Central team on recruitment@unisa.edu.au. Anything you tell us will be kept completely confidential.
Applications welcomed from Australian or NZ citizens, Australian permanent residents and those who have the legal right to work in Australia for the term of appointment.
CLICK HERE for Position DescriptionOpens in new window
How to apply:
Applications must be lodged online, please note UniSA does not accept applications via email.
- Start your application by clicking the ‘BEGIN’ button
- If you have already registered for an account, please login before starting your application
- If you have forgotten your log in details, click here to reset your password
- You will be able to save your progress throughout your application
UniSA is committed to developing a diverse workforce and a constructive enterprising culture in which everyone can thrive.
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