Project summary
This project explores how the brain constructs perceptual experience from visual input, focusing on the role of Bayesian models in perception. A key challenge in vision science is understanding how humans interpret complex scenes from the limited information available in retinal images. Modern theories suggest that perception involves probabilistic inference, where the brain integrates sensory signals with prior expectations to make sense of the world. However, the origins and nature of these expectations remain poorly understood.
This research aims to advance our understanding of perceptual experience by examining how structured patterns in visual input can inform models of perception. The work spans computational modelling and experimental approaches to uncover principles that explain how visual systems interpret properties such as shape, material, and lighting from images. By addressing fundamental questions about perception, this project will contribute to psychology, neuroscience, and artificial intelligence, offering insights into how biological and artificial systems can learn to interpret complex environments.
Applications close
20 April 2026 11:55pm
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Summary of position
We invite applications for a PhD scholarship to join a project investigating how perceptual experience arises from visual input, with a focus on Bayesian approaches to perception. The successful candidate will work within an interdisciplinary team at the University of the Sunshine Coast, contributing to research that combines computational modelling and behavioural experiments to understand visual cognition.
This position offers comprehensive training in advanced research methods, including psychophysics, eye-tracking, and computational approaches to perception. The project is suited to students with interests in cognitive neuroscience, vision science, and theoretical models of perception. The candidate will have opportunities to collaborate with leading researchers and engage with national and international networks.
This scholarship provides a unique chance to contribute to cutting-edge research on the foundations of perceptual experience, with potential applications in neuroscience, psychology, and artificial intelligence.
Ideal candidate
The ideal candidate will have completed Honours or a Master’s degree in Psychology, Cognitive Science, Neuroscience, or a closely related discipline, with a strong foundation in visual cognition and quantitative research methods.
- Advanced skills in experimental design and psychophysics, including stimulus generation and behavioural data collection
- Proficiency in programming for data analysis and modelling (e.g. MATLAB or Python)
- Familiarity with statistical modelling techniques (e.g. regression, mixed-effects models, or Bayesian approaches)
- Experience applying signal detection theory to analyse perceptual decision-making (highly desirable)
- Comfort working with computational modelling of perception or machine vision concepts
- Experience with image-processing methods and orientation analysis (desirable)
- Strong analytical skills and ability to work with complex datasets
- Experience with eye-tracking or neural data analysis (advantageous)
This position suits someone who can integrate theoretical knowledge with practical skills to investigate perceptual processes and contribute to the development of computational models of vision.
Inclusions and contact information
Package to support a Domestic Doctor of Philosophy (PhD) candidate:
- Stipend of $38,000 per annum (tax-free), paid in fortnightly instalments
- Tuition offset scholarship for 3 years to cover tuition fees (minimum value of $84,000)
- Relocation allowance of $2,000 (as per scholarship conditions)
The package is funded through the Australian Research Council and UniSC’s Research Training Program for 3 years, aligned with thesis submission (possible extension in line with relevant policies and procedures).
Domestic candidates must be Australian citizens, New Zealand citizens, or Australian permanent residents.
For questions or additional information, contact Dr William J Harrison at wharrison@usc.edu.au.