Available PhD projects - Engineering, architecture & IT

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Chief Investigator

Project title

Project description

Preferred educational background

Professor Kazuhiro Nogita

k.nogita@uq.edu.au

Next generation flexible high current micro-electronic interconnects

Because of economic and political pressure to reduce energy usage and the inclusion of smart functions in a wider range of applications, industry is searching for ways of reducing the process temperatures required for the manufacture of electronic circuity. The objective of the research is to develop a low temperature assembly process for electronic circuitry based on the bonding properties of Ga and Ga alloys. The intention will be to take advantage of the unique properties of intermetallic compounds formed by controlled reactions between Ga and circuit substrate materials that offer the possibility of high reliability connections.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

A background in materials science, mechanical engineering or chemical engineering. Analysis of interfacial reactions, intermetallic compounds, electronic assemblies and/or analysis of microstructure would be useful.

*The successful candidate must commence by Research Quarter 3, 2020. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons. 

Dr Hangil Park

hangil.park@uq.edu.au

Sensor development for mineral and coal processing

Monitoring slurry properties including solids concentration and particle size distribution is crucial in mineral and coal processing to maximise and maintain process efficiency.

This Ph.D project aims to develop an online sensor to monitor solids concentration and particle size distribution in slurry. Sensors with various signal processing algorithms will be developed and tested for real-time monitoring of slurry properties. A field test of the developed sensor will also be conducted to evaluate its performance. The outcome of this project will advance the process automation of mineral and coal processing operations.

The successful applicant will enrol through the School of Chemical Engineering.

Candidates should have an 1st class Honours or Master’s degree in:

  •  Chemical Engineering,
  • Mineral Engineering,
  • Metallurgical Engineering, or equivalent.

*The successful candidate must commence by Research Quarter 2, 2020. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons. 

Dr Miaoqiang Lyu

m.lyu@uq.edu.au

Low-cost and high-performance printed electronic devices based on metal halide perovskies

The rapid development in the areas of artificial intelligence and the Internet of Things (IoT) has attracted tremendous research interests in developing low-cost and high-performance electronic devices, including artificial electronic synapses, intelligent electronic sensory systems and non-volatile memory devices, and so on. The emerging metal halide perovskites hold great promise in realizing low-cost and high-performance electronic devices owing to their mixed ionic, electronic and photonic properties within one single material. In addition, these perovskites materials are solution-processable and can be crystallized at low-temperature, which shows potential to be combined with advanced printing techniques, such as inkjet-printing, screen-printing and roll-to-roll printing. The project will be focusing on exploring the potential of metal halide perovskites in the printed electronics for emerging artificial electronic synapses and next-generation IoT devices. The project will also explore the monolithic integration of the printed batteries with printed electronic devices to realize self-powered systems.

The successful applicant will enrol through the School of Chemical Engineering.

The candidate(s) will have a master’s degree or 1st Class Honours degree or equivalent in material/chemical engineering or electronic engineering. The students with electronic engineering background are highly preferred for this position, especially in electronic sensory devices. Mandatory requirements for international applicants 1. Peer-reviewed high quality journal publications or demonstrated practical experience in the relevant field; 2. Excellent academic performance evidenced by a high Grade Point Average (GPA).

*The successful candidate must commence by Research Quarter 2, 2020. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons. 

Professor Amin Abbosh

a.abbosh@uq.edu.au

Microwave Inspection and Detection Systems

This project aims at developing a microwave inspection system for the early detection of structural defects. The project aim will be achieved by combining innovative antenna array design, proper system integration, accurate electromagnetic modelling, and efficient  processing algorithms. 

The successful applicant will enrol through the School of Information Technology & Electrical Engineering.

Electrical Engineering with knowledge in applied electromagnetic and/ or microwave engineering. Basic knowledge of processing techniques will be desired.

*The successful candidate must commence by Research Quarter 3, 2020. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons. 

Dr Mingyuan Lu

m.lu1@uq.edu.au

Characterising interfacial adhesion using micro/nano-mechanical testing methodologies

Adhesion between metal thin film conductors and polymer substrates is a critical factor influencing the reliability of the emerging polymer-based flexible electronics. Hence, there is a compelling need to develop new methodologies for understanding the behavior of these metal/polymer interfaces.  This project seeks to elucidate and quantify the mechanical integrity of polymer-based flexible microelectronic interlayer systems. The aim is to develop an innovative methodology for measuring interfacial adhesion of conductive metal films on polymer substrates and to investigate the influence of interfacial adhesion on the electro-mechanical properties of the metal/polymer hybrid, using innovative in situ micromechanical testing procedures. Specific objectives are to

  • develop a novel reliable testing and characterisation toolkit for evaluating the adhesion of metal/polymer interfaces under tension and longitudinal and lateral shearing,
  • identify and quantify the fatigue mechanisms of these interfaces subjected to cyclic loading,
  • develop an in situ approach to examine the real-time effect of interfacial debonding induced mechanical failures on the conductivity of metal thin films on polymer substrates subjected to external loading, and
  • determine the relations between interfacial bonding, external loading, residual stresses in the films, deformation behaviour, delamination failure and electrical resistance of the metallic films.

 The methodologies will be a crucial enabler to accelerate the development of new flexible microelectronic technologies, from solar panels to electronic skin.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

Materials Science and Engineering and Material Mechanics

*The successful candidate must commence by Research Quarter 2, 2020. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons. 

Dr Adnan Trakic

a.trakic@uq.edu.au

Autonomous Microwave Inspection for Civil and Marine Industry

We are currently looking for a prospective PhD candidate to work on the development of novel robotically-assisted microwave inspection technology for automated and expedited image-based detection and diagnosis of deep-interior structural defects in civil and marine infrastructure, including buildings, roads and bridges.

This research project aims to obviate the need for current industry practices based on inaccurate and tedious manual inspections, effectively yielding billions in cost savings and reductions in hazard associated with unanticipated structural failures.

The combination of modern electromagnetic imaging techniques with robotic technology and machine learning algorithms is expected to pave a path for leading-edge systems and methods of the future.

The successful applicant will enrol through the School of Information Technology & Electrical Engineering.

First Class Honours or Masters degree in electrical or mechatronic engineering, or related field. Hands-on experience developing and programming electromechanical systems is preferred. Background in electromagnetics, as well as modelling and or programming skills are desirable.

*The successful candidate must commence by Research Quarter 1, 2020. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons. 

Dr Yifan Wang

yfwang@itee.uq.edu.au

Reconfigurable electromagnetic devices and beamforming systems for mm-Wave applications

In today’s Ka-band satellite communications-on-the-move (COTM) industry, one of the most significant evolutions for ground terminal design is to employ compact, low-profile, and reconfigurable flat-panel antennas (FPAs) as a replacement for their conventional counterpart, the dish antenna, dominated by its bulky parabolic reflector. Over the past three years, the design of Ka-band SATCOM FPAs has become one of the most attractive and best-supported R&D topics in the industry and the research community alike. Although the concept of generating a focused-beam through a planar-shaped antenna is not new, it is still extremely challenging to design a feasible FPA solution that meets the RF constraints, matches the market needs, and is commercially profitable.

This Ph.D. project aims to investigate a number of new approaches and develop an innovative reconfigurable/tunable electromagnetic devices in support of the proposed beamforming satellite terminal. A wide range of modern EM concepts and algorithms, such as modulated metamaterial, tunable holographic surface impedance, and array optimizations, might be utilized in this project.

The successful applicant will enrol through the School of Information Technology & Electrical Engineering.

Science or Engineering degree

*The successful candidate must commence by Research Quarter 1, 2020. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons. 

Dr Jiwon Kim

jiwon.kim@uq.edu.au

Data-driven Modelling of Urban Traffic Networks using Spatial Trajectory Data

This PhD project is part of an Australian Research Council (ARC) project titled “Data-driven Simulation of Large Traffic Networks using Trajectory Data”, which aims to provide transport planners and operators with a smart decision support tool that enables automated insight generation and data-driven decision making.

This project will develop an innovative traffic simulation platform that builds a traffic simulation model directly from data by inferring urban mobility patterns and behavioural rules underlying travellers’ decisions from large-scale vehicle trajectory datasets. The project tasks include the implementation of various machine learning technologies (including deep learning and reinforcement learning) to model interactions between vehicles and road networks and predict drivers' route choice behaviours and network traffic dynamics.

The successful applicant will enrol through the School of Civil Engineering.

Background in transportation engineering, computer science, data science, applied statistics or a closely related area

Excellent mathematical and statistical skills • Solid programming skills (e.g., Python, C++, R, Matlab)

Knowledge of machine learning and deep learning libraries (e.g., TensorFlow, PyTorch, Keras, scikit-learn)

Excellent oral and written communication skills in English

*The successful candidate must commence by Research Quarter 3, 2020. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons. 

Dr Guido Zuccon

g.zuccon@uq.edu.au

Searching when the stakes are high: better health decisions from Dr Google 

This project aims to help people make better health decisions from search engines. 80% of Australians use Dr Google despite evidence showing that many often find incorrect and unreliable health information, which can increase the severity of their health condition, ultimately increasing cost of healthcare delivery.

This project expects to provide new understanding about why and how people fail to find useful health information. Expected outcomes of this project are new models and methods for evaluating high-stakes search and new search technologies to help people find and recognise high quality information to make better health decisions. This should provide significant benefits to Australian health consumers and the healthcare system. 

The successful applicant will enrol through the School of Information Technology and Electrical Engineering.

Computer Science, Information Retrieval, Artificial Intelligence, Machine Learning

*The successful candidate must commence by Research Quarter 1, 2020. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons. 

Dr Jiwon Kim

jiwon.kim@uq.edu.au

Real-time Analytics on Urban Trajectory Data for Road Traffic Management

This PhD project is part of an Australian Research Council (ARC) Linkage project titled “Real-time Analytics on Urban Trajectory Data for Road Traffic Management”. The overall aim of this ARC Linkage project is to develop real-time analytics and data management capabilities that leverage large-scale urban trajectory data to provide road operators with real-time insights into population movements and enable data-driven, customer-centric network operations. Current traffic management practices rely heavily on aggregate vehicle count data from fixed road sensors, which have limitations in accurately measuring traffic demand and network congestion propagation. We seek to develop innovative technologies to use a wide variety of data sources, especially massive trajectories of vehicles moving across the network, to better understand people's travel demands and road usage patterns and thus better manage the transport system.

This PhD project will focus on one of the following objectives: (1) to develop methods to reconstruct complete, semantically rich trajectories of road users by combining raw trajectories from multiple data sources, (ii) to develop methods to estimate and predict dynamic movements of road users in real-time using multi-source trajectory data, and (iii) to develop network-wide traffic management strategies that leverage real-time population movement insights.

The successful applicant will work as a team with researchers from UQ Transport Engineering Group within the School of Civil Engineering and UQ Data Science Research Group within the School of Information Technology and Electrical Engineering, as well as industry partners from Queensland Department of Transport and Main Roads (TMR) and Transmax Pty Ltd.

The successful applicant will have flexibility to enrol through either the School of Civil Engineering or the School of Information Technology and Electrical Engineering.

• Background in transportation engineering, computer science, information technology, applied statistics or a closely related area

• Strong analytical skills including familiarity with a programming language such as Python, C/C++, R, or Matlab

• Excellent mathematical and statistical skills

• Excellent oral and written communication skills in English

 

*The successful candidate must commence by Research Quarter 3, 2020. You should apply at least 3 months prior to the research quarter commencement date. International applicants may need to apply much earlier for visa reasons. 

Professor Yusuke Yamauchi

y.yamauchi@uq.edu.au

and

Dr Shahriar Hossain

md.hossain@uq.edu.au
Nanoarchitectured Multifunctional Porous Superparamagnetic Nanoparticles

This project aims to develop a method for the direct detection of biomarkers based on a new class of highly porous superparamagnetic nanoparticles with peroxidase-like activity. The particles will be used as dispersible capture agents for isolating specific targets in biological samples, and electrocatalytic nanozymes for naked-eye evaluation and electrochemical detection. The project is expected to develop simple, low-cost, portable devices for the analysis of exosomes and exosomal miRNA in biological samples. The future development of this technology into diagnostic devices will improve patient outcomes by enabling earlier disease diagnosis and improved monitoring of treatment.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

MSc in materials science and engineering/bioengineering/ or related

Please contact the Chief Investigator to check on this project's availability.

Dr Guido Zuccon

g.zuccon@uq.edu.au
Reinforcement Learning and Online Learning to Rank for Systematic Literature Search

Online Learning to Rank (OLTR) aims to directly learn from user interactions in an online setting to overcome the limitations associated with offline LTR methods, such as the costs involved with creating datasets to train offline rankers and the lack of adaptation to changing query intents. This project aims to advance current state-of-the-art in OLTR, specifically by investigating methods from reinforcement learning and extending current evaluation frameworks for these techniques. The project will consider generic application areas in web search, and specific problems in the task of retrieving scientific literature for the production of (medical) systematic reviews – these tasks include both screening prioritisation (the ranking of scientific articles in answer to a query) and the ranking of queries within the query chain transformation framework developed by the ielab research team.

The successful applicant will enrol through the School of Information Technology and Electrical Engineering.

Required:

  • Honours or Masters in Computer Science or Information Technology with first class
  • Solid programming and algorithmic skills
  • Solid writing and communication skills

Preferred:

  • knowledge of Information Retrieval, Machine Learning, Reinforcement Learning demonstrated by relevant experience, courses, projects or publications.
  • Knowledge of machine learning and deep learning libraries, e.g., TensorFlow, scikit-learn.

Please contact the Chief Investigator to check on this project's availability.

Dr Ian Marquette

i.marquette@uq.edu.au
Quadratic algebras and their Casimir invariants

Quadratic algebras are generalisations of Lie algebras that have appeared in a variety of contexts of mathematical physics over the last 20 years. They play a central role in certain classes of exactly solvable systems, and are related to special functions and orthogonal polynomials in pure mathematics. This project aims to describe their universal enveloping algebras and obtain the so-called Casimir invariants.  

The successful applicant will enrol through the School of Mathematics and Physics.

Background in mathematics or physics.

Please contact the Chief Investigator to check on this project's availability.

Dr Ian Marquette

i.marquette@uq.edu.au
Indecomposable representations in exactly solvable models 

New types of infinite-dimensional representations of symmetry algebras have started to appear in conformal field theory and non hermitian quantum. This project aims to classify indecomposable representations beyond the so-called category O, by developing systematic approaches to differential operator realisations. This will involve generalisations of the familiar and ubiquitous hypergeometric functions. It will also facilitate the introduction of new exactly solvable models in statistical physics and quantum mechanics.

The successful applicant will enrol through the School of Mathematics and Physics.

Background in mathematics or physics.

Please contact the Chief Investigator to check on this project's availability.

Dr Christopher Leonardi

c.leonardi@uq.edu.au
Sustainable enhancement of coal seam gas production in Queensland

Approximately $300 billion of natural gas lies trapped within Queensland’s Bowen and Surat Basins, where current extraction technologies are ineffective. This project will develop a new technique for enhancing the gas transport and productivity in these coals via the exploitation of natural coal fractures and the novel injection of microparticles.

PhD Project 1: Linking the modelling and field diagnostics of hydraulic fracturing. This project will develop, implement, and apply large-scale computational models of hydraulic fracturing in naturally-fractured media (e.g. coals). History matching and or steering of the developed model(s) using diagnostic fracture injection test (DFIT) data, or similar, will also be performed.

PhD Project 2: Modelling the transport of complex particle suspensions in coals. This project will develop and validate new computational models of multiphase, non-Newtonian particle suspensions and apply them to study (a) microparticle injection and (b) gas production in naturally-fractured media (e.g. coals).

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

Honours or Masters degree in mechanical, civil, or petroleum engineering, applied mathematics or physics. Modelling and or programming skills desirable.

Please contact the Chief Investigator to check on this project's availability.

Dr Tushar Kumeria

t.kumeria@uq.edu.au
Bioresponsive Porous Silicon for Site Specific Oral Delivery of Antibodies for the Treatment of
Inflammatory Bowel Disease

This proposal aims to develop an oral antibody delivery system for treatment of inflammatory bowel disease (IBD) that affects 75000 Australians. The system will be based on porous silicon nanoparticles acting as container to protect the antibodies, and bioresponsive coatings acting as gates to enable site specific protein delivery at the inflamed site of GI tract. The project not only holds promise for protein delivery for the treatment of IBD but other diseases like diabetes. 

The successful applicant will enrol through the School of Pharmacy.

Materials engineering, porous nanomaterials, drug delivery, protein/biologics delivery. 

Please contact the Chief Investigator to check on this project's availability.

Professor Shazia Sadiq
shazia@itee.uq.eud.au

Dr Gianluca Demartini
g.demartini@uq.edu.au

Professor Marta Indulska
m.indulska@uq.edu.au
Crowd-sourced data curation processes

The capacity to effectively utilize the increasing number of datasets available to organisations for timely decision making, is diminishing due to onerous data preparation and curation tasks that have to be performed before the data can be consumed by analytics platforms. This project aims to tackle the growing problem of data curation, especially for repurposed datasets, by tapping into crowd intelligence. The project will be a first attempt at using a novel process-oriented approach in micro-task crowdsourcing, and will create new knowledge to harness the full potential of crowd sourced data curation.

The successful applicant will enrol through the School of Information Technology and Electrical Engineering.
  • Degree in Computer Science or related disciplines;
  • Strong programming skills
  • Ability to work independently
  • Excellent written and oral communications skills
  • Knowledge of formal research process including writing and presenting results/findings

Please contact the Chief Investigator to check on this project's availability.

Dr Julius Motuzas

j.motuzas@uq.edu.au
Inorganic membrane percrystallisation in hydrometallurgy

This project aims to develop a completely novel concept of using engineered inorganic membranes for the percrystallisation of strategic metal compounds in hydrometallurgical processes. The key research topics are precise tailoring of carbon structured membranes and the effect of membrane structure on crystal formation, separation and growth. These research topics will underpin the creation of novel engineered membranes that deliver high flux and crystallisation rates and provide the desired product qualities in hydrometallurgical applications.

The successful applicant will enrol through the School of Chemical Engineering.

The candidate(s) must have a master’s degree or 1st Class Honours degree or equivalent in chemical engineering or materials science.

Please contact the Chief Investigator to check on this project's availability.

Dr Hongzhi Yin

h.yin1@uq.edu.au
Meeting Challenges of Big Data for Cost-Effective, Scalable, Robust and Real-time Recommender Systems

This project aims to systematically study how to meet emerging challenges from “4Vs (Volume, Veracity, Variety, Velocity)” of big data and develop a scalable, robust and real-time recommender system framework in a cost-effective and end-to-end manner.

Specifically, our goal consists of subtasks: (1) developing a discrete latent factor model for scalable recommendation; (2) developing an anti-shilling model for robust recommendation; (3) developing a heterogeneous feature embedding and fusion framework to enhance the robustness for cold-start recommendation; (4) developing a reservoir sampling-based online learning scheme to support streaming recommendation.

The successful applicant will enrol through the School of Information Technology and Electrical Engineering.

1. Having a Master or Honours Degree in Computer Science, Data Science or Mathematics in Australia; or having Bachelor Degree obtained from other countries in equivalent academic areas.

2. Having the research background in Machine Learning, Recommender Systems, Data Mining, Information Retrieval and Natural Language Processing.

3. Being good at programming with deep learning packages, e.g., Tensorflow, Pytorch, etc.

Please contact the Chief Investigator to check on this project's availability.

Professor Ian Hayes

ian.hayes@uq.edu.au
Design and verification
of concurrent systems

This project aims to provide methods for the design and verification of correct, secure and efficient concurrent software that are scalable and mechanised. Computers with multiple processors are now the norm and are used in a wide range of safety, security and mission critical software applications such as transport, health and infrastructure. These multi-core architectures have the potential to lead to important efficiency gains, but can introduce complex and errorprone behaviours that cannot be managed using traditional software development approaches. This project will produce better, scalable and mechanised methods for the design and verification of such software which is expected to reduce the prevalence of failures in efficient, modern software.

The successful applicant will enrol through the School of Information Technology and Electrical Engineering.

Honours degree in software
engineering or computer science with a strong aptitude for mathematics.

Please contact the Chief Investigator to check on this project's availability.

Dr Xiaodan Huang

x.huang@uq.edu.au

High capacity and low cost rechargeable multivalent metal ion batteries

This project aims to develop advanced rechargeable multivalent metal ion batteries for renewable energy storage. Battery technologies are critical for the clean energy transformation in Queensland. Aluminium and zinc ion batteries are promising new energy storage systems, due to the natural abundance, high capacity and safety profile of aluminium and zinc. This project, in collaboration with FLEW Solutions - a Brisbane-based advanced manufacturing company, will develop new techniques to develop aluminium/zinc ion batteries.

The successful applicant will enrol through the Australian Institute for Bioengineering and Nanotechnology.

Materials science or Chemistry, a knowledge/ background in energy storage research would also be advantageous

Please contact the Chief Investigator to check on this project's availability.

Associate Professor Guy Wallis

gwallis@uq.edu.au
The role of non-visual cues in regulating perception and skilled movement

This project aims to investigate the impact of non-visual sensory information on what we see and how we control movement.

The successful applicant will enrol through the School of Human Movement and Nutrition Sciences.

Experimental psychology, Computer science and engineering, cognitive neuroscience.

Please contact the Chief Investigator to check on this project's availability.

Principal advisor: Dr William Harrison

w.harrison@uq.edu.au

Associate advisor: Professor Jason Mattingley

j.mattingley@uq.edu.au
The influence of naturalistic context on visual perception and memory

Human perceptual systems evolved and continue to develop in highly complex environments. The aim of this project is to understand how complex naturalistic context may influence neural processing of visual information. To address this question, the student will be trained to use a variety of methods, such as psychophysics, computational image processing, and statistical models. The student will use these tools to investigate how low-level (e.g. image statistics) and high-level (e.g. semantic content) image features influence the fundamental neural computations involved in visual processing.

The successful applicant will enrol through the Queensland Brain Institute.

This project is suited to anyone who wants to understand human cognition and perception, and who has an Honours or Masters degree in a field related to the following:  Cognitive Science, Psychology, Cognitive Neuroscience, Engineering, Maths. 

Although prior experience is not required, the project may appeal particularly to those interested in psychophysics, computational modelling, and programming in languages such as R and MATLAB.

Please contact the Chief Investigator to check on this project's availability.

Dr Yang Bai

y.bai@uq.edu.au
Designing new perovskite quantum dots for efficient solar energy conversion

This project aims to rationally design new perovskite quantum dots featuring prominent phase and thermal stability in humid air and remarkable optoelectronic properties, which will be crucial for the development of next-generation flexible, lightweight solar energy conversion devices.

The successful applicant will enrol through the Australian Institute for Bioengineering and Nanotechnology.

Physical chemistry,

Materials science,

Applied physics or chemistry

Please contact the Chief Investigator to check on this project's availability.

Professor John Zhu

z.zhu@uq.edu.au
Composites for Thermal Expansion Matched Oxygen Electrodes of Solid Oxide Cells

This project aims to develop high performance composite oxygen electrodes by using both negative thermal expansion materials and electrolyte materials to tailor the thermal expansivities and activities of the perovskite based electrodes for reduced temperature solid oxide cells . Such composite electrodes will show highly matched thermal expansion with  lectrolyte without sacrificing the high activity at reduced temperatures. This project thus addresses an important practical issue - thermal expansion compatibility, and is of great significance to the solid oxide cells industries. 

The successful applicant will enrol through the School of Chemical Engineering.

Chemical Engineering, Materials Engineering, solid oxide fuel cells, molecular simulations

Please contact the Chief Investigator to check on this project's availability.

Associate Professor Steven Pratt

s.pratt@uq.edu.au
Tough bio-derived and biodegradable wood plastic composites

High performance and cost-effective wood bioplastic composites: reinforcement with nanocellulose for a step-change in toughness.

The successful applicant will enrol through the School of Chemical Engineering.

Expertise in biotechnology, with experience in material processing and characterisation.

Please contact the Chief Investigator to check on this project's availability.

Dr Fred Roosta-Khorasani

fred.roosta@uq.edu.au
Efficient second-order optimisation algorithms for learning from big data

This project aims to apply a diverse range of scientific computing techniques to design and implement new, second-order methods that can surpass first-order alternatives in the next generation of optimisation methods for large-scale machine learning.

The successful applicant will enrol through the School of Mathematics and Physics.

MSc/MPhil degree with a mathematical component. Familiarity with optimisation algorithms. Good programming skills in Python.

Please contact the Chief Investigator to check on this project's availability.

Professor Justin Cooper-White

j.cooperwhite@uq.edu.au

Mimicking the perivascular niche with boronolectin-based biomaterials

This project aims to address roadblocks in perivascular stem cell manufacturing by discovering novel mechanisms and materials that improve cell quality outcomes during extended culture. An innovative, interdisciplinary, high throughput approach to biomaterials discovery, combining live cell-based screening of cell surface glycans, bio- inspired materials design and synthesis, and niche mimicry, will enable the discovery of cell surface glycan- mediated interactions that support long-term expansion and potency maintenance, and synthetic biomaterials that can mimic them. Significant benefits for stem cell researchers, manufacturers and end users are expected from these project outcomes and the application of this scalable biomaterial platform.

The successful applicant will enrol through the Australian Institute for Bioengineering and Nanotechnology.

Bachelor and/or Masters in  Bioengineering, Chemical or Materials Engineering (majoring in Biomaterials), Biotechnology.

* This project is available until December 2019 unless a suitable candidate is found prior.

 

Dr Jing Tang

jing.tang1@uq.edu.au

Structural and Compositional Controlled Carbon-based Nanocatalysts

This project involves interdisciplinary research pursuing highly efficient carbon-based electrocatalysts which are critical for developing clean energy technologies.

The successful applicant will enrol through the Australian Institute for Bioengineering and Nanotechnology.

  • chemistry
  • chemical eingineering
  • materials engineering

* This project is available until December 2019 unless a suitable candidate is found prior.

Professor Zhiguo Yuan

(contact person: Dr Bernardino Virdis b.virdis@uq.edu.au)

Methane Bioconversion to Liquid Chemicals – Creating Strong Economic Drivers for Biogas

This project aims to develop a suite of leading-edge biotechnology solutions to enable the cost-effective production of liquid chemicals from biogas. This will create a much stronger economic driver for biogas production from organic wastes, by significantly increasing the value of biogas compared to its current use for power generation. With a multi-disciplinary approach, the project will substantially advance the fundamental science in the exciting and highly valuable area of anaerobic microbial conversion of methane, the least understood process in the global carbon cycle. The project will support the establishment of a methane-based biotechnology sector creating high-value products from biogas or small, distributed natural gas sources.

The successful applicant will enrol through the School of Chemical Engineering.

Domestic applicants should have a B. Eng (Chem) or M. Eng (Chem) with 1st or 2ndA honours, or a B. Sc with a relevant major with 1st class honours. International applicants should have a masters degree in a discipline relevant to the project. 

* This project is available until December 2019 unless a suitable candidate is found prior.

Dr Yuanshen Lu

y.lu7@uq.edu.au

Artificial tornado enhancing  cooling towers/chimneys: mechanisms and engineering implementation

Stack effect is a fundamental physical phenomenon widely seen in air movements in building ventilation, chimneys, stacks, natural draft cooling towers (NDCTs), etc. Conventionally, industrial chimneys and NDCTs are built sufficiently tall (often > 100 m) to provide enough stack effect, or draught.

This project aims at an innovative way of draught enhancement in NDCTs inspired by tornados, a type of severe natural convective air vortex producing powerful lift. We preliminarily discovered that inducing swirling flow manually (artificial tornado) inside NDCTs can remarkably increase the upright draught, and consequently cooling performance of the NDCTs. This project will explore the fundamental mechanisms underneath and then the engineering approaches to realise and maximise this effect. The student is expected to conduct analytical/numerical and experimental studies.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

  1. A Master or Honours Degree in Engineering (Mechanical, Civil, Chemical, Aerospace, etc.) or Physics, with a good sense of mathematics and fluid mechanics.
  2. Better to have experience in CFD and/or experimental fluid mechanics.
*This project is available until November 2019 unless a suitable candidate is found prior.

Associate Professor Italo Onederra

i.onederra@uq.edu.au

Development of guidelines and tools to improve blasting outcomes and reduce geotechnical risks

The main objective of this project is to develop industry guidelines and practical tools to minimise geotechnical risks and improve blasting outcomes.

The project will focus on specific issues at mine sites by conducting field studies to quantify the impact of blasting strategies on geotechnical risks and mine productivity. The site related monitoring work will be complemented with an industry review; advanced modelling techniques and local site experiences.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

Engineering (Geotechnical, Mining, Civil, Mechanical)

*This project is available until November 2019 unless a suitable candidate is found prior.

Professor Damien Batstone

damienb@awmc.uq.edu.au

High efficiency conversion of syngas and carbon-dioxide based gases to biopolymers using phototrophic bacteria

Three PhD projects are available through this Australian Research Council funded project. This project will deliver efficient  processes for the large-scale production of biopolymers from low cost inputs, using phototrophic bacteria. Feedstocks include syngas from solid wastes and carbon-dioxide-hydrogen mixes from fossil and renewable sources. The choice of phototrophic bacteria avoids the energy losses associated with existing technologies, since photons are used instead of chemical energy for metabolic needs. This project enables the production and optimisation of biopolymers through collaborations between engineers, polymer scientists and molecular biologists. Together, we will deliver novel technologies to produce tough, flexible and affordable biopolymers, converting wastes and greenhouse gases to a valuable product. Specific PhD projects include laboratory and field scale process development, as well as metabolic and process modelling of production pathways.

The successful applicant will enrol through the School of Chemical Engineering.

Domestic applicants should have a B. Eng (Chem) or M. Eng (Chem) with 1st or 2A honours, or a B. Sc with a relevant major with 1st class honours. International applicants should have a masters degree relevant to the project.

*This project is available until November 2019 unless a suitable candidate is found prior.

Nanostructure Engineered Low Activation Superconductors for Fusion Energy

This project aims to develop a novel, low activation and liquid helium-free superconducting solution with superior electromagnetic, mechanical and thermal properties for use in fusion reactors.

Superconducting magnets and their associated cryogenic cooling systems represent a key determinant of thermal efficiency and the construction/operating costs of fusion reactors. The project expects to overcome these barriers so that widespread uptake of these reactors becomes viable.

Outcomes from the project will include a fundamental understanding of pure and doping-induced isotopic magnesium diboride superconductors and their behaviour under high neutron flux and harsh plasma atmosphere, which are specifically designed for application in next-generation, low-cost fusion reactors.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

  • Hold a Master degree in Materials Science and Engineering, Mechanical Engineering, Electrical Engineering, Applied Physics or related field
  • Strong background on magnetic and superconducting materials synthetic and characterisation
  • Hands-on experience on magnetic device manufacturing and cooling systems

*This project is available until December 2019 unless a suitable candidate is found prior.

Dr Tuan Nguyen
tuan.a.h.nguyen@uq.edu.au
 
Tailoring high strength geopolymer from iron-rich materials

The mistrust on the use of iron-rich materials in geopolymeric cement and concrete development has restricted the use of enormous geological resources. Ferrous compounds in these precursors are suspected to have harmful actions that block the geopolymerisation and reduce the geopolymer's compressive strength. Using both experimental and theoretical modelling approaches at multiscale, this project will exploit the geopolymerisation mechanism of the binding phase (Na,K,Ca)-poly(ferro-sialate) to tailor high strength geopolymeric materials.

The successful applicant will enrol through the Sustainable Minerals Institute.

Applicants should have a degree in Chemical Engineering or Mechanical Engineering with a strong interest in Physics, Mathematics, and Material Synthesis. It would be better if the applicants have MPhil or equivalent degree.

*The successful candidate must commence by Research Quarter 2, 2020. You should apply at least 3 months prior to the research quarter commencement date. International students may need to apply much earlier for visa reasons. ​

Dr Michael Taylor

m.taylor@sbs.uq.edu.au

Brillouin microscopy to study cell biomechanics

A Brillouin microscope measures sample stiffness and viscosity using only light, and thereby allows detailed mechanical studies with high resolution in inaccessible regions such as the cell interior. This project implements new techniques and data analysis in Brillouin microscopy to improve sensitivity and speed, for use in cellular biomechanics.

The successful applicant will enrol through the Australian Institute for Bioengineering and Nanotechnology (AIBN).

Physics or Engineering. Experience and interest in optics, signal processing, or biomechanics is an advantage

*This project is available until December 2019 unless a suitable candidate is found prior.

Professor Victor Rudolph

v.rudolph@uq.edu.au

A skid-based transportable plant for PFAS contaminated site remediation

This Research activity aims to develop a self contained skid-based transportable process for onsite destruction of toxins at contaminated sites. The process will permit remediation of these sites by completely converting all toxins in to safe products: mainly carbon dioxide and harmless salts.

The successful applicant will enrol through the School of Chemical Engineering.

Chemical engineering, membrane based water purification (RO, nanofiltration)

*This project is available until December 2019 unless a suitable candidate is found prior.

Dr Nadeeka Dissanayaka

n.dissanayaka@uq.edu.au

Virtual Reality in Residential Aged Care

Virtual reality (VR) is an emerging field within residential aged care for the management of behavioural and psychological symptoms in residents. This project will develop and test a suit of VR applications in RAC facilities.

The successful applicant will enrol through the Faculty of Medicine.

A background in Psychology, design and virtual reality applications is desirable.

*This project is available until December 2019 unless a suitable candidate is found prior.

Professor Han Huang

han.huang@uq.edu.au

Removal mechanisms and innovative technologies for machining gallium oxide wafers

The deformation and removal mechanisms of single crystal β-Ga2O3 are not well understood. The lack of such understanding has hindered the development of the cost-effective machining processes for it and thus, more widespread application of the β-Ga2O3 based electronic devices. To overcome this ‘bottleneck’ problem, a comprehensive and systematic study of the deformation and removal mechanisms under mechanical loading needs to be carried out in order to develop cost-competitive technologies for machining single crystal β-Ga2O3 wafers.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

Applicant should have a research background in mechanical engineering. It would be better if the applicant has got a MPhil or equivalent

Professor Mingxing Zhang

mingxing.zhang@uq.edu.au

 

Professor Xue Li

xueli@itee.uq.edu.au

Design of New Generation High Performance Aluminium Alloys using Big Data Analytics 

This project aims to address a long-term problem to effectively discover new alloys and processes using big data analytics. It expects to develop a few new and high-performance aluminium alloys through interdisciplinary research and to generate new knowledge in the area of materials science from investigation of the strengthening and toughening mechanisms.  The intended outcomes also include a validated a big data analytic model for new alloy development, which further enhances the interdisciplinary collaboration.  The high performance aluminium alloys should provide significant benefits to automotive and aerospace industries as these sectors target at improving fuel efficiency through weight reduction at lower cost.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

Engineering, IT

Associate Professor Adrian Cherney

a.cherney@uq.edu.au

Optimising illicit dark net marketplace interventions

UQ PhD scholarship in illicit dark net marketplace interventions ($26,288 per year). This ARC Linkage project is a collaboration between the University of the Sunshine Coast, the University of Queensland, the University of Southampton and a range of industry partners that includes the Queensland Police, iDcare, Australia Post, Department of Immigration and Boarder Protection, and the Australian Crime Commission. The project draws on systems based analysis to assess illicit dark net forums and identify how personal information is stolen, bought and sold on the dark net. Outcomes include developing and testing a series of interventions designed to disrupt identify theft activities.  The project brings together researchers, practitioners, theories and methods from human factors, sociotechnical systems, criminology, and cyber security. One aim of this PhD is to examine the semantic and organisational structure of illicit dark net forums. The project is led by the University of the Sunshine Coast (USC) in partnership with iDcare (https://www.idcare.org/) and it is expected the PhD student will need to spend at least 2 days week at USC working with the project team. 

The successful applicant will enrol through the School of Social Science.

Background in criminology and cyber security /information technology

Professor Matt Dargusch

m.dargusch@uq.edu.au

Advanced Functional Materials

This project is focussed on developing new functional materials.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

Chemical, Materials or Mechanical Engineering

Professor Matt Dargusch

m.dargusch@uq.edu.au

New Generation Biocompatible Materials

This project is focussed on the development of New Manufacturing Processes and Materials for biomedical applications.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

Biomedical, Chemical, Materials or Mechanical Engineering

Professor Matt Dargusch

m.dargusch@uq.edu.au

Machine Learning in Manufacturing

Defect Detection in Medical Devices using Machine Learning Strategies.

The successful applicant will enrol through the School of Mechanical and Mining Engineering.

Mechanical, Mechatronics/Electrical Engineering or similar

Dr Joel Carpenter

j.carpenter@uq.edu.au

Control of light in space and time in multimode optical fibres

Controlling the way light propagates in space and time using digital holography.

Enabling applications such imaging deep into ‘opaque’ objects such as human skin or brain, high-power lasers for material processing and manufacturing, optical telecommunications, and quantum computation. Project includes industry collaboration with Nokia (Bell Labs) and Finisar, as well as University of Southampton.

The successful applicant will enrol through the School of Information Technology and Electrical Engineering.

Honours/Masters in Physics, Electrical Engineering or similar discipline. Strong programming skills desirable.

Professor Jonathan Corcoran

jj.corcoran@uq.edu.au

Reclaiming lost ground: Transitions of mobility and parking

Car mobility and immobility (i.e. parking) are persistent urban problems. Considering new transitions and trends in land-use and transport, including car-sharing and automated vehicles, and the revival of urban living, important questions arise concerning the redesign and reuse of urban space. Policy-makers need a new evidence base and toolkit to determine how best to repurpose the space currently dedicated to accommodating private motor vehicles to make cities more attractive, efficient and liveable places. This project’s overall aim is to understand the role of parking in mobility, urban consolidation, and transit-oriented development. Does parking supply affect travel demand, car ownership, and ultimately the quality of urban life?

The successful applicant will enrol through the School of Earth & Environmental Sciences.

A background in urban planning or human geography, preferably with some training in spatial data and analysis.

Associate Professor Yan Liu

yan.liu@uq.edu.au

New approaches to modelling human-environment interactions for sustainable coastal city development

This project aims to model sustainable development options of low-lying coastal cities under rapid population growth, climate change and intensive human activity. Using Brisbane (Australia) and Ningbo (China) as case studies, the project will empirically test and understand how cities grow as complex systems built out of the interactions between humans and their living environment at the individual scale and in a cross-jurisdictional context. The project expects to offer a spatially explicit understanding of the development of coastal cities and science-based decision tools to improve policy-making.

PhD project 1: Modelling human-environment interactions: Testing irregular CA and 3D urban models. This PhD project will develop and test an irregular CA model to align with land cadastre boundaries, and a 3D CA model structure to account for the vertical growth of cities.

PhD project 2: Modelling human-environment interactions: A cross-cultural comparison. The project will focus on developing applications of the CA-ABM in a coastal city in China, and comparing the modelling approach, performance, and outcomes under different cultural, policy and institutional settings.

The successful applicant will enrol through the School of Earth & Environmental Sciences.

GIS; Human geography; Urban studies/planning; Geoinfomatics; or other relevant field.