PhD Projects SEIT

Scholarships of $35,000 (AUD) are available for PhD students  who have achieved Honours 1/High Distinction in their UG program and/or have completed a Masters by Research.

Multisource big spatial data analysis

The field of earth observation (EO), or remote sensing, is now facing significant challenges in the processing of image data for end user purposes because of the rapidly escalating numbers of missions and sensors, and because of the range of different types of sensor being orbited.

Microwave and Millimetre-wave Metasurfaces

Metasurfaces are a promising new area of science and technology for the manipulation of electromagnetic waves. They have the potential to replace bulky devices such as lenses with a thin layer of patterned elements, to enable a wave to undergo focussing, steering, polarisation conversation and more general spatial/temporal filtering.

Wave impact loads

This project aims at addressing the lack of high-quality three-dimensional data suitable for benchmarking offshore structures and advanced marine vehicles impacting with water in a 3D regime, as well as establishing an understanding of the key elements influencing the severity of slamming loads. It also aims to evaluate the accuracy of numerical techniques by utilising Computational Fluid Dynamics (CFD) simulations to predict the magnitude of wetdeck slamming forces and pressure distributions, thus allowing designers to improve the fixed, floating and moving marine structures.

High-bandwidth control for unmanned helicopters

This PhD work is a part of the project to develop high bandwidth control methods and advanced dynamic modelling for Rotorcraft Unmanned Aerial Vehicles (RUAVs). This will enable new roles such as the precision landing of RUAVs to the moving deck of a ship in rough seas. This and numerous other potential RUAV tasks are presently limited by the simple controllers used for such a responsive dynamic system.

Investigating Best Practices in Human-Systems Integration and Engineering Methodologies

This project aims at identifying current state of the art human systems integration techniques and creation of framework for an overarching or generalized human system integration framework that can be substantiated for different kinds of systems. Human systems integration practices are very domain specific for example healthcare, defence, aerospace etc.

Real-time Distributed Lifelong Optimisation Algorithms for Swarm Intelligence

A swarm is a group of decentralized decision nodes that need to coordinate and synchronise actions to achieve an effect. One example is in computer Ad-hoc networks where the nodes need to swarm to maximise network throughput. This project aims at designing and proving optimality conditions for new optimisation algorithms.

An FRP sandwich structure consists of two high strength composite skins separated by a core material. Inserting a core material between the laminates increases the stiffness of the panel without increasing its weight. FRP sandwich panels are very popular in the aerospace and automotive industries, and various core materials, such as balsa, PVC, PET, honeycomb, are available to satisfy the needs of these industries.

Satellites provide data and services that are essential to modern society. Our civilian, commercial, and defence capability rely on continued and assured access to space-based infrastructure. The space environment, however, is harsh and represents a significant threat to the operation of such satellites. Collision with space debris, damage to spacecraft components through electrostatic discharge, and communication disruption from atmospheric anomalies are daily threats facing satellite systems and their operators.

An Integrated Stakeholder Preference Modelling and Tradespace Evaluation Framework

This project’s aim is to facilitate optimal decision making for multi stakeholder system design. This study will investigation available preference modelling methods and asses their utility for integration with Tradespace exploration techniques.

Urbanization monitoring using multisource remote sensing imagery for the development of smart cities

With the increasing availability of remote sensing data recorded from multiple sources, comprehensive digitalization of urbanization processes becomes possible, aiming to provide quantitative information for smart city development. Most of the existing approaches for urbanization monitoring, however, are based on individual sensors with limited observation.