Postdoctoral Researcher

PRIMARY DETAIL

· Salary Package: From $106,08 to $113,697 (Level A), plus 17% employer's superannuation and annual leave loading
· Appointment Type: Full-time, 12 month fixed-term role
· Location: Macquarie University (Wallumattagal Campus, North Ryde)

Macquarie University is seeking a highly motivated postdoctoral researcher with expertise in machine learning, particularly in learning for neural fields. This position offers an exciting opportunity to collaborate on cutting-edge research at the intersection of machine learning and partial differential equations (PDEs), with a specific focus on reaction-diffusion systems.

About the Role

The successful candidate will work closely with our team to develop innovative techniques for studying pattern formation dynamics in reaction-diffusion systems. By leveraging modern machine learning tools, we aim to create new methodologies for analyzing and predicting complex spatiotemporal behaviors that arise in these systems. The project is led by Associate Professor Leo Tzou (University of Melbourne) and Dr. Justin Tzou (Macquarie University). While the successful applicant is expected to be based at Macquarie University, Sydney, flexibility for splitting time between Macquarie University and the University of Melbourne is possible depending on individual circumstances.

Key Responsibilities:

• Conduct research on machine learning techniques applicable to neural fields.

• Develop and implement novel algorithms for studying reaction-diffusion dynamics.

• Collaborate with experts in PDEs and reaction-diffusion systems to integrate domain knowledge with machine learning approaches.

• Publish findings in high-impact journals and present results at international conferences.
   

Qualifications:

• PhD in Machine Learning, Applied Mathematics, Computational Science, or a related field.

• Strong background in deep learning, neural fields, or physics-informed machine learning.

• Basic knowledge of PDEs.

• Knowledge of differential geometry is desirable.

• Experience with reaction-diffusion models or related dynamical systems.

• Proficiency in programming languages such as Python, TensorFlow, or PyTorch.

• Excellent communication and teamwork skills.
   

What We Offer:

• A stimulating research environment with opportunities for interdisciplinary collaboration.

• Access to high-performance computing resources.

• Competitive salary and benefits.

• The possibility of extending the position based on performance and funding availability.
   

How to Apply:

To be considered for this position, please apply online by submitting the following documents:

• Resume

• Cover Letter detailing your research experience and interests, along with information for at least two references

We welcome applicants from international candidates.

Appointment Type: Full-time, 12 month fixed-term role

Specific Role Enquiries: Dr. Justin Tzou at justin.tzou@mq.edu.au.

General Recruitment Enquiries: Kate Williams, Talent Acquisition Consultant, at k.williams@mq.edu.au.

Applications close: Thursday 27th of March at 11:59PM (AEDT)

*** Applications will be reviewed on a rolling basis. We reserve the right to progress or decline an application prior to the advertised closing date .

If you're already part of the Macquarie Group (MQ University, U@MQ, MQ Health, MGSM), you'll need to apply through your employee Workday account. To apply for this job: Login to Workday and go to the Careers App > Find Jobs.

Applications Close:

27/03/2025 11:59 PM

Diversity and Inclusion

Innovation and ingenuity thrive at Macquarie University when diversity, equity and inclusion take centre stage. At the University, we embrace a culture where diversity of background, experience and perspective are fundamental to our success.

We do not discriminate on gender identity, age, culture, disability, sexuality, Indigeneity, family and caring responsibilities or religion. See our journey towards leadership in Equity, Diversity and Inclusion in Higher Education.

Flexible Work
 

At Macquarie, we believe by providing flexibility in when, where and how work is done, we can support our staff to manage their personal commitments, while optimising their work performance and contributions to the University. See how we lead in flexible work to enable an outcome focused and inclusive workplace. To learn more about our culture and hiring process, explore our Candidate Resource Hub.