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Computational communication and culture

The Computational Communication and Culture research program within the Digital Media Research Centre investigates how rapid advances in computation and human-machine communication are transforming society, through automation and AI, the Internet of Things, and disintermediating technologies such as blockchain. We draw on and extend computer science and critical humanities theory and methods (including agent-based modelling, machine vision, critical simulation, and information visualisation) to help explore and explain emergent phenomena in the digital media environment, including the fundamental transformation of communication …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Creative Industries, Education and Social Justice
School
School of Communication
Research centre(s)
Digital Media Research Centre

Hierarchical visualisation of large social networks

Networks have been extensively used to capture social interactions, by representing individuals as nodes and their relationships as edges.Such networks have been used to model the spread of epidemics. A few nodes are 'infected', and over time they gradually infect their neighbours on the network, who in turn infect their neighbours, etc. This type of model can then be used to simulate different intervention strategies aimed at containing outbreaks.However, an important limitation is the difficulty to visualise these networks when …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science
Research centre(s)
Centre for Data Science

Statistical methods for detecting Antarctic ecosystems from space

Satellite images are a frequent and free source of global data which can be used to effectively monitor the environment. We can see how the land is being used, how it’s being changed, what’s there – even where animals are in the landscape. Using these images is essential, particularly for regions where data is expensive to collect or difficult to physically access, like Antarctica. In Antarctica and the sub-Antarctic islands, satellite images can be an easy and quick way to …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Forecasting disease spread risk based on human movement patterns

This project aims to forecast the risk of infectious disease spread, such as COVID-19 and dengue, based on human movement patterns. We'll use multiple data sources that describe people movement in order to understand individual and population level mobility patterns, and use empirical disease case data to model the effect of movement on the spread of disease.

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Computer Science

Topics in computational Bayesian statistics

Bayesian statistics provide a framework for a statistical inference for quantifying the uncertainty of unknowns based on information pre and post data collection.This information is captured in the posterior distribution, which is a probability distribution over the space of unknowns given the observed data.The ability to make inferences based on the posterior essentially amounts to efficiently simulating from the posterior distribution, which can generally not be done perfectly in practice.This task of sampling may be challenging for various reasons:The posterior …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Predicting player performance from one format to another in cricket

Identifying talent as early as possible in elite sport is critical. An important component of this is learning about what metrics of performance in lower grades to focus on to help predict performance in the top grade. This project will explore for this research problem for cricket.

Study level
Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

Giant viruses in the human gut microbiome

The human body is home to a vast ecosystem of microorganisms including bacteria, archaea, fungi, viruses, and bacteriophages that make up the human microbiota. These microbes and their collective genetic material, known as the microbiome, influence a wide range of physiological functions including nutrient production and absorption, the development and regulation of our immune system, protection against potential pathogens, and even our mood and mental health. While distinct microbial communities exist throughout the body, the gut microbiome has gained particular …

Study level
Master of Philosophy, Honours
Faculty
Faculty of Health
School
School of Biomedical Sciences
Research centre(s)

Centre for Microbiome Research

The Law and Policy of Satellite and Large Data in Environmental and Land Use Management

Dr Evan Hamman is looking for PhD/MPhil candidates wanting to explore the relationship between space technologies and large data sets in the mapping, managing and directing of human land use. Candidates interested in exploring the relationships between land use management, data science and environmental law and regulations are particularly encouraged. The focus can be Australia, comparative or public international law. This topic is led by the QUT School of Law within the Datafication and Automation of Human Life research group. …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Business and Law
School
School of Law

Digitising Legislation

Dr Anna Huggins is looking for PhD/MPhil candidates interested in the emerging computational law project of translating legislation into digital forms. This could involve top down conceptualisation of the translation of legislative provisions or projects examining in detail the digitisation of specific legislation. Candidates with a background in data science, public administration and/or law are encouraged to apply. This topic is led by the QUT School of Law within the Digital Social Contract and Datafication and Automation of Human Life …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Business and Law
School
School of Law

Taxonomy of data science methods

To reap the benefits of data science it's necessary to be able to pair real world data problems with data science methods.In this project we'll begin to map out the key methods, their benefits and drawbacks, and suitability of each given some initial problem statements.

Study level
Vacation research experience scheme
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science

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