PhD – Causality and Prediction Modelling for Assets with Real-time Data

• Research
• Position based at The University of Melbourne
• abbas.r@unimelb.edu.au

The Centre for SDIs and Land Administration (CSDILA) at the University of Melbourne invites potential applicants for postgraduate (PhD) study to conduct research in Causality and Prediction Modelling with Real-time Data for assets and infrastructure as part of an Australian Research Council (ARC) Research Hub Resilient and Intelligent Infrastructure Systems (RIIS). RIIS aims to deliver transformational technologies to address Australia’s critical infrastructure needs. It will integrate advances in real-time data modelling, sensor technology, connectivity, and machine learning to deliver resilient and adaptive infrastructure systems in urban, energy and resources sectors.

Entry Requirements and Scholarships

It is anticipated that successful applicants should meet the following requirements:

• Applicants must have previous Honours or Masters Qualifications and preferably work experiences in real-time data processing, analytics and modelling, causality analysis, prediction modelling, or relevant disciplines, with a demonstrated focus in research and development on real-time data reasoning and decision making.
• Applicants must demonstrate that they meet the entry requirements for a PhD degree in Engineering and apply for scholarships at the Faculty of Engineering and IT. The University of Melbourne provides scholarships for academically outstanding applicants. Further details are available at:

https://study.unimelb.edu.au/find/courses/graduate/doctor-of-philosophy-engineering-and-it/

Required Skills

• Experienced in event streaming technologies and protocols (e.g., Kafka, MQTT, etc.)
• Demonstrated skills in programming languages for real-time data modelling  (e.g., Python, R, Java, etc.)
• Knowledge of causality and prediction modelling with machine learning and deep learning methods.
• Interest and ability to contribute to the cutting-edge research by publishing articles in reputable scientific journals and conferences.
• Strong time management abilities as well as strong interpersonal and communication (both written and spoken) skills for a broad range of audiences.
• Self-motivated, highly committed to assigned tasks, and perform independent research activities.
• Highly enthusiastic to explore new ideas and highly adaptive to undertake new research challenges.

Desired Skills

• Experienced in IoT and Digital Twin integration
• Knowledge of industry automation systems
• Knowledge of SCADA or similar systems

How to Apply

In the first place, interested applicants should submit their CV and transcripts (both Masters and Bachelor’s), and a short statement on their motivation for this research to the project supervisors:

• Prof Abbas Rajabifard (Hub Deputy Director),     email    abbas.r@unimelb.edu.au
• A/Prof Jagannath Aryal (Chief Investigator),        email    jagannath.aryal@unimelb.edu.au