Research Fellow Job No.
: 670987 Location: Clayton campus Employment Type: Full-time Duration: 20 months fixed-term appointment Amplify your impact at a world top 50 University Join our inclusive, collaborative community Be surrounded by extraordinary ideas - and the people who discover them Monash University's Faculty of Information Technology is seeking a Level A Research Fellow to join the Department of Data Science and Artificial Intelligence (DSAI).
This role offers an exciting opportunity to contribute to cutting-edge research focused on optimisation technology and its application in architectural design.
About the Role: You will work on a dynamic project aimed at developing automated optimisation approaches to enhance building design coordination, addressing inefficiencies that arise when diverse expertise ( structural and mechanical engineering) intersects during the design process.
This role involves developing optimisation models ( using MiniZinc) and solving methods to demonstrate the transformative potential of optimisation technology in this application.
Collaboration will be key, as you'll join the DSAI's optimisation team while liaising with industry partners to align research goals with their priorities.
There will also be opportunities to publish findings in leading optimisation venues.
Key Responsibilities: Develop and test optimisation models and solving methods to demonstrate their application in design processes.
Collaborate with the DSAI team and industry partners to ensure the research aligns with project objectives and industry needs.
Contribute to high-quality research outputs, with an expectation to publish in relevant academic venues.
The ideal candidate will have: A strong background in mathematical optimisation or computational problem-solving.
Experience with optimisation tools such as MiniZinc or similar platforms.
Proven ability to work independently and collaboratively on research projects.
An enthusiasm for interdisciplinary collaboration and application of research to real-world challenges Symbolic knowledge representation and reasoning, including temporal logics and Answer Set Programming (ASP) in the context of neural-symbolic systems Discrete optimization and/or Boolean satisfiability Exact and approximate model counting About Monash University At Monash, work feels different.
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Together with our commitment to academic freedom, you will have access to quality research facilities, infrastructure, world-class teaching spaces, and international collaboration opportunities.
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Monash supports flexible and hybrid working arrangements.
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