UNSW Scientia PhD Scholarship Scheme

The UNSW Scientia PhD Scholarship Scheme is part of our dedication to harnessing our cutting-edge research to solve complex problems and improve the lives of people in local and global communities. Scientia scholars will have a strong commitment to making a difference in the world with demonstrated potential for contributing to the social engagement and/or global impact pillars of the UNSW 2025 Strategy.

The Scientia Scheme is targeted in that applicants will apply to a specific research area with an identified supervisory team and application is by nomination. If you would like more information about the Scientia PhD Scholarship scheme, please visit UNSW Scientia Scholarships.

PhD Projects

The impact of technological innovations on the passenger process

Supervisory Panel: Prof Gabriel Lodewijks, Prof Ann Williamson, Dr Fangni Zhang.

Over the last ten years significant technological innovations were introduced on airports, including self check-in systems and biometric based security systems. These innovations had a significant impact on the so-called passenger process. Where technology-savvy young passengers can deal with these innovations relatively easily, for elderly people, people with physical constraints, illiterates or people that seldom travel it may be very hard to adapt to the new equipment and changing procedures. In this project the passenger process will be redesigned from the point of view of the passenger taking into account human capacities and limitations and social background.

Since this research project is about the impact of technological innovations on the passenger process at airports, the ideal candidate will have a strong engineering or science background and a solid interest in human factors. She or he will have done projects that involved (automated) technology, human aspects in the transportation field. The ideal candidate has published journal papers and has a strong interest in developments towards “a just society”.

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Pilots' mental health: An independent and comprehensive investigation

Supervisory Panel: Assoc/Prof Brett Molesworth, Assoc/Prof Jessica Grisham, Prof Peter Lovibond.

Germanwings Flight 9525 in 2015 where the first officer deliberately flew into the French Alps, killing all aboard highlights the growing problem of pilot mental health in commercial aviation. According to the Federal Aviation Administration in the US, aircraft assisted pilot suicide is common. Little is known however about pilot mental health, including source of stress, triggers, and coping strategies. Hence, the aim of the proposed research is to develop a comprehensive understanding about pilots’ mental health, including: sources of stress (occupational and domestic), significant life events, job satisfaction, demographic factors, and coping strategies that relate to pilot mental health.

This project is suited for a student with a psychology background (clinical, applied, and/or experimental) and an interest in clinical psychology including: assessment, diagnosis, and treatment. Technical skills required for the project include: knowledge of clinical assessment techniques, data analysis (e.g., SPSS).

Desired skills: knowledge of aviation.

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Understanding pilot skills using naturalistic flying data

Supervisory Panel: Dr Carlo Caponecchia, Dr Soufiane Boufous, Prof Jason Middleton.

Globally there is a critical shortage of trained pilots. Understanding how pilot skills develop is important for refining training programs to increase their effectiveness and address this gap. This project will use naturalistic data recorded during training flights to map critical stages in pilot training and development. This will help understand what pilots do in real baseline flying scenarios, especially at approach and landing; how behaviours change over time; factors that influence the achievement of key training milestones; and appropriate performance feedback. These data will lead to new methods of learning support, training delivery and performance monitoring of trainee pilots.

The ideal candidate will have a background in either human factors or behavioural sciences, with some experience in manipulating and analysing large data sets.

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Data Driven Cycling Safety Policy

Supervisory Panel: Dr Soufiane Boufous, Prof Ann Williamson, Prof Christopher Pettit.

Improved cycling safety is necessary to meet the global road safety goal of reducing road deaths, a major public health issue. It is also vital to increasing cycling participation as an effective way to improve physical and mental well-being as well as the quality of the environment. This project seeks to investigate how policy makers in Australia and elsewhere use and translate traditional sources of data (i.e. police crash data and cyclist surveys) to develop cycling safety policy. It also explores the potential of new sources of information such as fitness tracking and route mapping smartphone applications in this area.

The project will be suitable for a candidate with a good understanding of the collection and use of large administrative data sets in the development of public policy, particularly in the areas of public health and road safety. Specific skills include undertaking interviews and focus groups as well as basic quantitative and qualitative data analyses. Knowledge of data collections using smartphone applications would be an advantage.

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Exploring the Capacity of tourism Activities for Indigenous Heritage Sites

Supervisory Panel: Dr Taha Hossein Rashidi, Dr Reuben James Bolt, Dr Tay Koo.

Tourism and Indigenous communities have separate and often conflicting concerns regarding tourism activities on traditional lands. To appropriately unlock the huge potential of tourism requires in-depth understanding of both perspectives. This research aims to develop a new and eclectic set of capabilities for building sustainable tourism development in Indigenous heritage sites. A mathematical system of models of tourist flow and spending in Indigenous heritage sites will be developed. You will be part of an interdisciplinary team that will be the first to attempt to formalise the multifaceted, social, spatial and temporal tourist choices and their inter-relations using a technique known as activity-based modelling at a national scale.
The ideal candidate will have:

  • Strong mathematical background
  • Strong background in statistics
  • Good understanding about economics and behavioural sciences
  • Solid understanding about survey design and data analysis
  • Some programming capacity

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Managing human mobility in smart cities

Supervisory Panel: Dr Wei Liu, Dr Lauren Gardner, Dr Tay Koo.

The increasingly digital nature of urban infrastructures and services is radically changing the way we work, live and travel, and bringing about novel data availability for urban systems. This project, by utilizing multiple sources of big data, will quantify human activity and mobility patterns in two scales: within-city and inter-city, and then develop integrated approaches for within-city and inter-city human flows. At the strategic level, this project will further optimally plan infrastructures and services including ground and air transport, food supply resilience and security, healthcare facilities and services, and public health applications, to promote urban liveability and sustainability.

Applicants should hold a degree in a relevant discipline (e.g. computer science, information engineering, industrial engineering, transport and logistics, statistics, applied mathematics) with excellent English communication skills. The student should be highly motivated with an interest in and understanding of computational modelling and simulation. Experience in computer programming (e.g. Python, C++, R, MATLAB), data visualization, numerical methods would be considered a strong advantage.

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