PhD – Developing Predictive Models and Tools for Real-Time Flood Monitoring FEIT

• Research
• Position based at The University of Melbourne
• jagannath.aryal@unimelb.edu.au

Take the opportunity to do your PhD at the University of Melbourne, Faculty of Engineering and IT (FEIT) with the Centre for SDIs and Land Administration (CSDILA).

This PhD position forms part of a significant national research hub, the ARC Research Hub: Resilient and Intelligent Infrastructure Systems (RIIS) RIIS.org.au

Description

The Centre for SDIs and Land Administration (CSDILA) at the University of Melbourne invites potential applicants for postgraduate (PhD) study to conduct research in Predictive Models and Tools for Real-time Flood Monitoring 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. This PhD project will make use of live flood data to create Australia’s first Dynamic Digital Twin. The focus of this project will be on real-time sensor data analytics of flood affected locations. The location will include an entire catchment thus providing a rich database that can be used for a wide range of infrastructure protection plans. Candidates with a background in Geomatics, Earth Observation, Remote Sensing, IoT or related fields are welcome to apply.

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 Geomatics, 3D Geospatial Data Modelling, Building Information Modelling (BIM), or relevant disciplines, with a demonstrated focus in research and development on assets or infrastructure.
• 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

• Demonstrated skills in programming languages for real-time data modelling  (e.g., Python, R, Java, etc.)
• Demonstrated knowledge on prediction modelling with machine learning and deep learning methods.
• Demonstrated knowledge on spatial granularity and image processing
• Knowledge of sensor networks and Internet of Things (IoT)
• Demonstrated publication records or high potential to publish the cutting-edge research in reputable scientific journals and conferences.
• Strong time management capabilities along with strong interpersonal and communication skills (both written and spoken) 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 Spatial Data Analytics, IoT and Digital Twin integration.
• Knowledge on sensor device design and their functioning

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