Postdoctoral Fellow

Classification: Academic Level A
Salary package: $91,546–$114,906 per annum plus 17% superannuation
Terms: Fixed term, Full-Time (approximately 11 months from 1 February 2027)

Join us in developing a new digital therapeutic for depression through closed-loop non-invasive brain stimulation as the next generation Australian national critical research infrastructure. The Postdoctoral Fellow in Machine Learning Engineering role exists at the School of Computing in the ANU Neuroinformatics group and is research intensive in an externally funded Medical Research Future Fund (MRFF) grant project across the University in Computer and Health Sciences. Applications are particularly invited from researchers in Data Science and Analytics who undertake high-impact collaborative and transdisciplinary Software Engineering and Machine/Deep Learning Research in Health and Medical Informatics.

About the School

The School of Computing has a strong foundation in computing and information sciences at ANU. We are a transformative centre for research in artificial intelligence and machine learning, computer systems and software, and theoretical foundations of computing. We span traditional and modern thinking, connecting decades of computer science methodologies with modern data and computational science. Our mission is motivated by the need to design, drive and sustain strategic activities via five broad focus areas: Computing Foundations, Computational Science, Intelligent Systems, Data Science and Analytics, and the Software Innovation Institute. Be part of an innovative and forward-looking intellectual agenda, built on a diverse, inclusive culture.

About the College

As one of the great universities of the world, ANU is driven by a culture of excellence in everything we do. Our lived experience is increasingly one of large-scale systems of people, whose actions and interactions are influenced by our digital, physical and biological environment. The ANU College of Systems and Society (CSS) hosts many of the key disciplines necessary to help us design, build, regulate and secure the future.

CSS brings together expertise in social, technical, computational, ecological and scientific systems to build a new approach to systems design and build new national capabilities in data-driven policy and business development. The work we do in the College is to strengthen our national mission and meet our unique responsibilities as Australia’s national university. We will deliver on our mission by building a strong community, providing transformative educational experiences, conducting high-impact research, seeking meaningful engagement, and becoming a resilient organisation.

We welcome and openly acknowledge differences in expertise, research / education / professional focus, experience and perspective.

CSS is a vibrant and diverse community of more than three thousand students, staff, and visitors. Our College is comprised of the School of Computing, School of Cybernetics, School of Engineering, Fenner School of Environment & Society, Mathematical Sciences Institute, and the Australian National Centre for the Public Awareness of Science, supported by the Professional Services Group.

Enquiries

To enquire about this role, please email Professor Hanna Suominen: hanna.suominen@anu.edu.au.

Our commitment to diversity, belonging, inclusion and equity

ANU is committed to building a diverse and inclusive community, and particularly welcomes applications from women, Aboriginal and Torres Strait Islander people and candidates from culturally and linguistically diverse backgrounds. Furthermore, it is practice in the ANU College of Systems and Society to actively seek a gender mix of shortlisted candidates for interview. For more information about staff equity at ANU, visit https://services.anu.edu.au/human-resources/respect-inclusion

We welcome and develop diversity of backgrounds, experiences and ideas and encourage applications from individuals who may have had non-traditional career paths, who may have taken a career break, had career disruptions or who have achieved excellence in careers outside of the higher education sector. We support applicants who require flexible arrangements in their work environments or patterns. If your experience looks a little different to what we’ve described, but you’re passionate and motivated by this position, we welcome your enquiry and application.

For more information about staff equity at ANU, click here. For enquiries about the application process, or if you require reasonable adjustment to apply for this role, please contact the hiring manager on the above listed details.

What we offer

The ANU provides attractive benefits and excellent support to maintain a healthy work/life balance and offers generous remuneration benefits, including four weeks paid vacation per year, assistance with relocation expenses and 17% employer contribution to superannuation. We also offer generous parental leave, the possibility of flexible and part time working arrangements, a parental and aged care support program, dual career hire programs, staff and family tuition fee discounts, ANU school holiday programs, and childcare facilities on campus. For more information, visit: https://services.anu.edu.au/human-resources

How to apply

Applicants must apply online via the ANU recruitment portal and should upload the following separate documents:

• A detailed curriculum vitae (CV) including a full publication list and the names and contact details of at least three referees (preferably including a current or previous supervisor). If your CV does not include referees, you can complete these online when prompted in the application form.
• A short statement addressing the selection criteria (max 3 pages).
• A statement outlining your research objectives (max 2 pages).
• A showcase of your past project(s) in Machine Learning Engineering. This can be in the form of a link to your published code OR a short video (no more than 3 minutes) OR slides (no more than 3 slides) OR other ways you think is best to showcase your past project(s).

Applications which do not address the selection criteria may not be considered for the position.

Please note: The preferred candidate must have rights to live and work in Australia and will be required to complete mandatory pre-employment declarations and background checks relevant to the role they have applied for, in accordance with the Background Checking Procedure and the National Higher Education Code to Prevent and Respond to Gender-Based Violence.