QUT offers a diverse range of student topics for Honours, Masters and PhD study. Search to find a topic that interests you or propose your own research topic to a prospective QUT supervisor. You may also ask a prospective supervisor to help you identify or refine a research topic.
Found 713 matching student topics
Displaying 181–192 of 713 results
Where should we put our sensors? Designing smarter water quality monitoring networks
Water utilities and environmental agencies face a deceptively simple question: where should we put our sensors? In a piped stormwater network, the question matters because finding an illicit discharge quickly depends on having the right sensors at the right places. In an open creek or river, the question matters because spatial coverage, transport dynamics, and cost trade-offs all influence whether monitoring will actually answer the question being asked.Decisions about sensor placement are still often made on the basis of accessibility, …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
Smart triggered sampling: low-cost devices and intelligent retrofits for capturing the moments that matter
Many water quality issues are event-driven. The most informative signals often appear during short windows associated with storms, illicit discharges, first flush, or operational upsets. Capturing these windows is genuinely hard. Manual sampling is often too slow, especially overnight or during fast-changing events. Conventional autosamplers help, but they are large, power-hungry, and typically deployed only at major assets, leaving smaller drains, tributaries, pump stations, and pollution hotspots without coverage. Even when an event is captured, fixed-interval sampling fills bottles after …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
See it without touching it: low-cost non-contact sensing for our waterways
Many of our most important waterbodies, including reservoirs, lakes, lagoons, wetlands, sedimentation basins, and constructed wetlands, are still monitored using sparse in-water sensors and periodic grab sampling. These methods are costly to maintain, hard to scale across many sites, and often miss spatially variable changes in water quality.Non-contact sensing offers a different approach. Cameras, spectral sensors, radar, thermal imaging, and other sensing modalities can observe water from outside it, reducing fouling, simplifying servicing, improving worker safety, and enabling broader spatial …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
Rapid pathogen detection in water: from lab prototype to field-ready public health tool
Faecal contamination is one of the most consequential water hazards because it directly affects public health. Beach closures, do-not-drink advisories, and waterway warnings all depend on detecting microbial contamination quickly and reliably. Today, monitoring still depends largely on infrequent sampling and laboratory turnaround times that arrive long after the contamination has come and gone.Direct microbial sensing has advanced through biosensors and microfluidics, but most concepts remain at low technology readiness and are rarely demonstrated as field-usable systems. Reliability in the …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
Smart sensing for nutrients in our waterways: low-cost continuous monitoring for pollution tracking and real-time control
Nitrogen and phosphorus are central to the health of stormwater systems, rivers, wetlands, and lakes. They drive algal growth, oxygen stress, and downstream ecological impacts, and they are a key input to environmental reporting and catchment management. Yet most monitoring still relies on infrequent grab samples that miss the short pollution pulses that matter most.The challenge is delivering nutrient monitoring that is affordable, low-maintenance, and reliable enough for continuous deployment across many sites. Existing nutrient sensors are often too expensive …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
Designing Inclusive Sports Technology for Broader Participation in Physical and Digital Sporting Environments
Sport and active participation play a critical role in physical health, social inclusion, wellbeing, and community connection. However, many people continue to face significant barriers to participation, including people with disabilities, and individuals experiencing mobility, sensory, cognitive, social, or economic constraint. Emerging sports technologies present new opportunities to broaden access and participation, yet many products, services, and systems remain designed for narrow user groups and performance contexts.This PhD project will investigate how sports technologies can be designed to support more …
- Study level
- PhD
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
- QUT Design Lab
Design Lab
Designing perception: Investigating gender perception in designed objects through practice-based research
Perceptions of gender are not limited to people; they extend to objects, products, and environments through subtle interactions between form, language, and cultural context. The inclusion and arrangement of specific aesthetic attributes are a primary driver of perceived object gender, interacting with various factors, including cultural and personal individual identity. This creates an opportunity to reframe the question of “object gender” through a design research lens.This PhD project seeks to explore object gender through practice-based design research. It leverages user …
- Study level
- PhD
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Design
- Research centre(s)
- QUT Design Lab
Design Lab
Learning complex dynamics from multimodal time-series data
Modelling non-stationary dynamics from high-frequency time-series data remains challenging. These signals often exhibit complex temporal and spectral structure, while observations are typically noisy, incomplete, and affected by changing operating conditions, making reliable prediction and representation learning difficult.This PhD project, offered at Queensland University of Technology (QUT) in collaboration with industry partners, focuses on learning representations and dynamics from multimodal time-series data.The research will explore deep approaches including sequence models, transformer-based architectures, anomaly detection, graph neural networks, and self-supervised learning, with …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Journey mapping student experiences in engineering education
This research topic explores the use of journey mapping as a research and design methodology to better understand, analyse and improve student experiences in engineering education. The project investigates how students navigate key stages and touchpoints across the academic lifecycle including transition into university, curriculum progression, assessment, engagement, wellbeing and career development. By systematically mapping these journeys, the research aims to reveal patterns, barriers, and opportunities that shape student engagement, experience and success.Situated at the intersection of engineering education research, …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
Educator capability development and recognition in engineering education
This research topic examines educator capability development and recognition in engineering education, with a particular focus on the misalignment between the skills increasingly required of educators and the ways those skills are formally recognised and rewarded in higher education.Building on contemporary scholarship in engineering education and academic career development, the project explores how expectations around teaching quality, digital capability, assessment design, and evidence‑based practice have expanded—while promotion, workload, and recognition frameworks have not always kept pace.The research aims to inform …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
Emerging technologies and data-driven learning in engineering education
This research topic explores the use of emerging technologies and data‑driven approaches to enhance learning and teaching in engineering education. The project investigates how diverse educational data sets can be leveraged to support evidence‑based decision making across multiple levels of the institution—from individual educators and course teams to faculty leaders and senior executives. The work sits at the intersection of engineering education, learning analytics, and strategic use of educational data to improve student engagement, experience, and success.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Mechanical, Medical and Process Engineering
- Research centre(s)
- Centre for Data Science
Energy transitions in the food sector: how AI shapes consumer behaviour over time
Energy transitions are often studied in sectors such as transport (e.g. electric vehicles) and housing (e.g. solar panels, batteries), where decisions are relatively infrequent, highly deliberative, and associated with clear long-term payoffs. In contrast, food consumption represents a fundamentally different energy-relevant sector: decisions are made daily or even multiple times per day, involve low deliberation, and prioritise immediate outcomes such as convenience, cost, and taste (Reisch, 2021). These characteristics make food systems particularly susceptible to short-term decision-making, where long-term energy …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
- Research centre(s)
- Centre for Future Enterprise
Energy Transition Centre
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