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E-Coach-supported Digital SlEEp Therapy for Older ADults with Cognitive Impairment – the ExCEED Study

We are seeking a Master/PhD student to conduct a three-part study: (a) user experience qualitative study of older people's perceptions of Sleepfix; (b) randomised control trial of t more...

Supervisor(s): Gordon, Christopher (Dr), Hoyos, Camilla (Dr)

The relationship between sleep, vascular disease and Alzheimer’s biomarkers in older adults at risk of dementia

Sleep plays a vital role in brain health, cognition and everyday functioning and increasing evidence suggests that sleep disturbance is a new risk factor for dementia. Embedded with more...

Supervisor(s): Naismith, Sharon (Professor)

What are the best tools to assess people with substance use disorders?

The aim of this research project is to review the available tools used to assess a range of factors relating to substance use disorder (e.g., screening, substance use, treatment eff more...

Supervisor(s): Monds, Lauren (Dr)

Optimal model of follow-up care after treatment of localised melanoma

Most melanomas are detected by patients or family members between scheduled visits; even more might be detected if patients are trained in how to self-examine their skin and have a more...

Supervisor(s): Dieng, Mbathio (Dr)

Development of Tissue-Targeted Vectors for Musculoskeletal Gene Therapy

A unique opportunity is available for an outstanding PhD scholar to conduct research in developing tissue-targeted AAV vectors for gene delivery and CRISPR gene editing. more...

Supervisor(s): Schindeler, Aaron (Associate Professor)

Development and evaluation of an educational online repository of short, focused, peer-created teaching videos, in the Sydney Medical Program.

This Masters opportunity pertains to the development and evaluation of an educational online repository of short, focused, peer-created teaching videos in the Sydney Medical Program more...

Supervisor(s): Nanan, Ralph (Professor), Lane, Stuart (Associate Professor)

ARTIFICIAL INTELLIGENCE/MACHINE LEARNING ASSISTED NEWBORN CRITICAL CARE (VIRTUAL CRITICAL CARE MODELING)

The most vulnerable critical care patients are newborn babies both those extremely premature and sick full term. High resolution physiological data is displayed for all patients but more...

Supervisor(s): McEwan, Alistair (Professor)