"Lecturer Level B (Academic) in Data Science and Statistics"

About the Role

This role offers the opportunity to contribute meaningfully to the University of Newcastle’s mission of delivering excellence in education, research, and professional service. Working within the School of Information and Physical Sciences, you will play a vital part in advancing strategic priorities and delivering high-quality outcomes that support students, staff, and the broader community.

The successful candidate will develop high quality research and deliver excellent teaching in key areas within the Data Science, Computing, and Statistics program/discipline areas. You will be required to develop international recognition as an innovator in new Statistical methodologies, with applications to many fields of data analysis. The role requires a person who is comfortable with the development of new theoretical advances and with the translation of new methods in applied research.

You will be joining a community of professionals who are passionate about creating a better future for our regions and the world. You will be supported by a dynamic and inclusive workplace culture that encourages growth, innovation, and meaningful impact.

About you

You are dedicated and forward-thinking with a strong academic background in Data Science, Statistics or an equivalent relevant field. You bring strong foundations teaching Data Science and Statistics related courses in a tertiary environment with experience conducting meaningful research to attract research funding.

You thrive in collaborative settings and are committed to fostering an inclusive and equitable learning and research environment. You value diverse perspectives and actively contribute to a culture that supports mutual respect, innovation, and continuous improvement.

To be successful in this role, you will also have:

• A PhD in Data Science, Statistics, or equivalent relevant field.
• A strong publication record relative to opportunity.
• Ability to be a highly effective teacher in a tertiary environment, preferably with experience in teaching Data Science and Statistics related courses at the University level.
• Demonstrated ability to supervise research students at both undergraduate and postgraduate levels.
• Demonstrated ability to conduct impactful research to attract industry/government research funding.
• Expertise or experience in the development and delivery of online and blended courses.
• Willingness and ability to contribute to outreach activities, governance, organisational administration (including course coordination) and initiative/activities within the University.
• Highly developed interpersonal skills including the ability to participate in a team environment demonstrating clear communication and mutual respect.

For the full list of essential and desirable selection criteria, please review the Position Description.

About Us

The School of Information and Physical Sciences is a vibrant hub for innovative education and impactful research. As part of the College of Engineering, Science and Environment, we prepare students and researchers to be visionary thinkers, tackling tomorrow’s complex challenges today.

We offer flexible and future-focused programs across disciplines including Computer Science, Cyber Security, Data Science, Information Technology, Mathematics, Physics, Software Engineering, and Statistics. Our graduates are equipped with the analytical and technical skills needed to thrive in dynamic industries such as fintech, AI-driven manufacturing, digital health, and renewable energy.

Our research is globally recognised, contributing significantly to the University’s international reputation. With strengths in applied mathematics, machine learning, space sciences, and more, we foster interdisciplinary collaboration to address scientific and technological challenges.

How to Apply

If viewing this on a job board other than the University's please click ‘Apply’ to be redirected to our website, where you can review the full Position Description and submit your application.

Your application must include:

• Your ORCID ID.
• A URL link to your University Academic Profile (or equivalent).
• A Cover Letter and Statement (uploaded as a single PDF):
  • Cover Letter (max. 1 page) outlining your interest in the role and providing details of 3 referees.
  • Statement (max. 4 pages) addressing the Essential and Desirable Criteria, as listed in the position description.
• Your CV (max. 5 pages) tailored to your discipline

Please visit here for a guide on how to apply for a role. It’s important you read this information to ensure you are providing all the requirements of your application.

For specific position enquiries, please contact Professor Karen Blackmore, Head of School at karen.blackmore@newcastle.edu.au or on 0249215206.

Application close date: Sunday 11th January 2026 at 11.59pm AEDT