"Postdoctoral Research Associate"

Full time, 2-year fixed term position. Located on the Darlington Campus for the School of Civil Engineering

Opportunity to help scale breakthrough hydrogen storage technology through advanced automation in clean energy manufacturing

Base Salary $113,400 - 151,328 (Academic Level A/B) + 17% superannuation

About the opportunity

Hydrogen (H2) is widely recognised as a clean energy vector essential for decarbonising hard-to-abate sectors. Currently the large-scale deployment of hydrogen remains constrained by the limitations of storage technologies, which rely on either high-pressure compression or cryogenic liquefaction-both of which are energy-intensive, costly, and pose significant safety risks. Rux Energy (Rux) is addressing this challenge by commercialising a breakthrough hydrogen storage solution based on patented nanoporous materials.

Rux are at an exciting point in scaling their manufacturing processes, and in order to achieve a cost-competitive product this process must be optimised. Automation plays a significant role in improving efficiency, cutting costs, and streamlining the manufacturing process at scale. This project will build on our current capabilities to utilise automation to collect, process, and analyse data in the manufacturing process.

The project is a partnership between Rux Energy and USYD and is a multi-disciplinary effort between scientists and engineers. We are looking for a Postdoctoral Research Associate to work within the project to bring innovation to different aspects of the project. We offer immersive support from prestigious academic supervisors and industry leaders. If you are passionate about research, but want to see your ideas become reality, this is the project for you.

Your key responsibilities will be to:

Phase 1: Manufacturing data integration

The first phase of this project will involve identifying, sourcing, and installing various sensing equipment in Rux's in micropilot plant. The data from these sensors will be integrated into an existing platform composed of open-source, commercial and in-house developed software. Finally, QC points and a live process tracking system will be developed by extending the existing platform through adoption or development of new components.

Phase 2: Using big data insights to optimise the manufacturing process

The second phase of this project will focus on processing and utilising machine-learning techniques to analyse large volumes of data from sensors installed in Phase 1. The aim will be to merge the QC points and tracking system developed in Phase 1 with AI to develop predictive maintenance capabilities and extract insights about the manufacturing process, such as:

• Identify any key parameters in the mfg process that impact material performance
• Optimise power/energy usage throughout the process

The outcome will be to optimise the manufacturing process on the micro-pilot scale to improve efficiency and product quality.

About you

• PhD in data science or mechanical/chemical/computer engineering or related area
• digital twin and systems engineering, with the ability to model, simulate, and optimise complex manufacturing processes
• industrial automation engineering, including designing, integrating, and improving automated systems for scalable production
• data ingestion, analysis, and visualisation, turning raw manufacturing data into actionable insights for process optimisation
• software development, particularly using Python, JavaScript, and HTML/CSS to build tools, automate workflows, and support data-driven decision making
• excellent communication and report writing skills, enabling clear documentation, effective collaboration, and high quality technical reporting.

How to apply

Applications (including a cover letter, CV, and any additional supporting documentation) can be submitted via the Apply button at the top of the page.

For employees of the University or contingent workers, please login into your Workday account and navigate to the Career icon on your Dashboard. Click on USYD Find Jobs and apply.

For a confidential discussion about the role, or if you require reasonable adjustment or any documents in alternate formats, please contact Nicole Turle, Recruitment Operations by email to nicole.turle@sydney.edu.au

Applications Close
Sunday 18 January 2026 11:59 PM