Exercise Sciences

Applications are now closed

Effects of hypnotic susceptibility on movement performance


Supervisor

Associate Professor Greg Anson

Dr John Cirillo

Dr Alexa Srzich

Discipline

Exercise Sciences

Project code: SCI138

This exciting project is suitable for a student with an interest in, and aptitude for, movement neuroscience. The scholar will undertake this project in movement neuroscience, working alongside postgraduate and postdoctoral movement neuroscientists, in the Movement Neuroscience Lab. This project is best suited for students who have successfully completed EXERSCI 305 – MOVEMENT NEUROSCIENCE. Further details about this exciting project can be obtained by emailing Associate Professor Greg Anson after Sept 15th

Movement Neuroscience


Supervisor

Professor Byblow

Discipline

Exercise Sciences

Project code: SCI139

This exciting project is suitable for a student with an interest in, and aptitude for, movement neuroscience. The scholar will undertake this project in movement neuroscience, working alongside postgraduate and postdoctoral movement neuroscientists, in the Movement Neuroscience lab. This project is best suited for students who have successfully completed EXERSCI 305 – MOVEMENT NEUROSCIENCE.

Further details about this exciting project can be obtained by emailing Professor Byblow after Sept 15th.

Project in Neuromechanics


Supervisor

Dr Angus McMorland

Discipline

Exercise Sciences

Project code: SCI140

This exciting project will explore an important issue in the field of neuromechanics, the nexus between computational neuroscience and biomechanics.

Our lab explores how the healthy brain control controls movement, how that can be disrupted in disease, in particular after stroke, and how new technology can be applied to improve the quality of life of those with movement disorders. The recipient will work alongside postgraduate and postdoctoral movement neuroscientists in the Movement Neuroscience lab.

The project will best suit students with a demonstrated interest in at least some of the following: movement, neuroscience, quantitative analysis, and coding skills. Students who have completed EXERSCI 305 – MOVEMENT NEUROSCIENCE, EXERSCI 303 – BIOMECHANICS II, engineering, computer science or mathematics courses are particularly encouraged to apply. To discuss project specifics, contact Dr McMorland in person.

Classification of frailty status among older adults based on behavioural and clinical measurements


Supervisor

Yanxin Zhang

Borja del Pozo Cruz

Discipline

Exercise Sciences

Project code: SCI141

Frailty is a medical syndrome associated with various behavioural and clinical factors. The aim of the project is to use machine learning algorithms to classify frailty status among older adults based on different measurements (fitness, body composition, behaviour variables, clinical and demographic variables). This project is suitable for a student with an interest in clinical physiology, rehabilitation, quantitative data analysis, and public health. Further details about this exciting project can be obtained by emailing Dr Yanxin Zhang or Dr Borja del Pozo Cruz after Sept 15th