Student topics

The fundamental idea behind the ML approach is to analyze and map the relationships between the physical,chemical, and energy storage properties of materials with their associated output data. This early understanding of the energy storage capabilities through the ML approach helps the material scientists to clearly understand, discover, and optimize the fabrication process to develop highly efficient energy storage systems. It also provides key steps in the device fabrication process omitting excessive experimental stages.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Chemistry and Physics

Research centre(s)

Centre for Materials Science

The lithium-metal battery (LMB) has been regarded as the most promising and viable future high-energy-density rechargeable battery technology due to the employment of the Li-metal anode. However, it suffers from poor energy density and safety, and improved battery design is sought. The anode-free full-cell architecture is constructed from a fully lithiated cathode with a bare anode Cu current collector. In such an anode-free lithium battery, both the gravimetric and volumetric energy densities can be extended to the maximum limit. Moreover, …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Chemistry and Physics

Research centre(s)

Centre for Materials Science

Mixed polyanionic compounds have been studied extensively as viable cathode materials for sodium-ion batteries. Mixed phosphates Na4M3(PO4)2P2O7 (M = Mn2+, Fe2+, Co2+, Ni2+), provide a low barrier for Na-ion diffusion, being advantageous in comparison to phosphates and pyrophosphates. Despite being structurally similar, electrochemical performance differs for their analogues with different degrees of (de)sodiation, according to the transition element present. This project will develop series of mixed phosphates using novel rapid heating methods to achieve desired electrochemical properties.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Chemistry and Physics

Research centre(s)

Centre for Materials Science

Mathematical models of particle transport are fundamental to many applied disciplines including physics, biology, ecology and medicine. Particle transport is typically modelled using either a stochastic model, where probability rules govern the motion of individual particles, or a continuum model, where partial differential equations govern the concentration of particles in space and time. This project aims to use analytical and numerical techniques from applied and computational mathematics to address one or both of the following questions:what is the average time …

Study level

Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Mathematical Sciences

Monte Carlo methods use random sampling to approximate solutions to challenging problems. These methods are helpful for statistical models with many parameters, as discussed in this short video. The methods are particularly useful for Bayesian inference where one wishes to get a rigorous understanding of parameter uncertainty.Despite having many advantages over their competitors, Monte Carlo methods can be very slow in the context of big data. In this project, you'll help develop scalable Monte Carlo methods to enable timely and …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Mathematical Sciences

Research centre(s)

Centre for Data Science

The tricuspid valve is responsible for regulating the flow of blood between the right atrium and the right ventricle of the heart. During ventricular systole, it closes to prevent the backflow of blood from the right ventricle into the right atrium. This closure ensures that blood is pumped forward into the pulmonary circulation. In contrast, the tricuspid valve opens during ventricular diastole, allowing blood to flow from the right atrium into the right ventricle.When the tricuspid valve fails to close …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Mechanical, Medical and Process Engineering

Research centre(s)

Centre for Biomedical Technologies

Stochastic simulation-based models are routinely used in many areas of science to describe inherent randomness in many real-world systems. Applications include the study of particle physics, imaging if black holes, biochemical processes, the migration of animals, and the spread of infectious diseases. To apply these models to interpret data requires statistical methods to estimate model parameters.Unfortunately, standard statistical techniques are not capable of analysing data using these models. This is largely due to the model likelihood, the probability of the …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Mathematical Sciences

Research centre(s)

Centre for Data Science

This student research topic focuses on exploring and developing immersive systems that facilitate interactions between novice and expert users in the context of complex remote data analysis. The goal is to design and prototype innovative solutions that enhance the collaboration, learning, and training aspects of data analysis tasks.The research will involve investigating various immersive technologies and their potential application in bridging the gap between novice and expert users, enabling effective knowledge transfer and skill acquisition.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Computer Science

Green infrastructure refers to public and private green spaces in cities that provide water cycle benefits. These green spaces range in the range from single trees on city streets to urban parks, and waterway walkways. Some are natural, such as the remains of native plants, while others are more geometric, for example green roofs and green walls. Green infrastructure can increase the sustainability and vitality of cities through benefits such as greening and cooling, water quality, and managing hotter weather. …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Architecture and Built Environment

As social media becomes more intertwined into our daily lives, having an online presence on social media has become common not just in the private but also in the public sectors. The use of social media in local governments has shown great potential in terms of improving the efficiency and effectiveness of citizen-government communication. It has also been effective in terms of increasing citizen engagement and participation. Therefore, this research project seeks to discover how do local governments leverage the …

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Engineering

School

School of Architecture and Built Environment

Investigate the potential applications of RPA/ Process Automation in the healthcare sector. Explore how RPA/Process Automation can streamline administrative tasks, improve patient data management, enhance healthcare delivery processes, and support clinical decision-making. Address the challenges and opportunities of implementing RPA in highly regulated environments like healthcare.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Information Systems

Examine the ethical and legal implications of RPA/Enterprise Automation adoption in organisations. Research can focus on addressing issues such as data privacy, transparency, accountability, and the impact of RPA/Automation on human employment, culture, and structure.

Study level

PhD, Master of Philosophy, Honours

Faculty

Faculty of Science

School

School of Information Systems

Research centre(s)

Centre for Behavioural Economics, Society and Technology