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Psychology & Psychiatry PhD Projects, Programs & Scholarships in Manchester

We have 22 Psychology & Psychiatry PhD Projects, Programs & Scholarships in Manchester

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Showing 1 to 10 of 22
  Characterising coordination difficulties in autism using computational techniques
  Dr E Gowen, Dr E Poliakoff, Dr A Casson
Applications accepted all year round

Funding Type

PhD Type

Autism is a life-long developmental condition that affects how a person communicates and interacts with people. ~80% of autistic individuals also have altered motor control such as less accurate eye-hand coordination and abnormal gait patterns, causing considerable problems with activities of daily living.
  What is the best way for healthcare professionals to communicate changes in estimated risk of breast cancer?
  Prof D French, Prof G Evans
Applications accepted all year round

Funding Type

PhD Type

Risk estimation models for common multifactorial diseases such as breast cancer are often used, e.g. in Family History Clinics to inform decisions about prevention options.
  Perceptual stability in Virtual Reality across the adult lifespan
  Dr P Warren, Dr R Champion
Applications accepted all year round

Funding Type

PhD Type

When we move, stationary parts of the world around us move on the retina. Of course, usually we correctly interpret this retinal motion as due to our own movement and not movement of the surrounding environment.
  Machine Learning and Cognitive Modelling Applied to Video Games
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

Video games have been viewed as an ideal test bed for the study of AI. However, most of the academic work in this area focused on traditional board and card games where limited AI techniques have been tested.
  How do people move from contemplating to attempting suicide: Investigating the cognitive mechanisms of loss of control and limited awareness of goals
  Dr D Pratt, Dr W Mansell, Dr S Tai
Applications accepted all year round

Funding Type

PhD Type

Suicide is a leading cause of death and it remains unclear how individuals transition from contemplating suicide (ideators) to attempting suicide (attempters).
  Improving the lives of older adults with hearing loss: Developing a self-report measure of effortful listening to guide clinical practice
  Dr A Heinrich, Prof K Munro, Dr R Millman
Applications accepted all year round

Funding Type

PhD Type

Hearing loss is the most prevalent sensory deficit. In the UK, more than 10 million adults have a hearing loss. Because it is often associated with old age and the size of the older population is growing, it is predicted that there will be more than 14 million people with a hearing loss by 2030.
  Investigating the attentional consequences of the uncanny valley
  Dr E Poliakoff, Dr E Gowen, Dr C Capek
Applications accepted all year round

Funding Type

PhD Type

The “uncanny valley” was hypothesed by roboticist Mori in 1970, whereby people would like robots of increasingly human-likeness until they were close to, but not fully human.
  Triggering movement in Parkinson’s through imagery and observation
  Dr E Poliakoff, Dr E Gowen, Dr P Warren
Applications accepted all year round

Funding Type

PhD Type

Parkinson’s disease is one of the commonest neurodegenerative diseases, which profoundly affects movement. Typically, a person is slower to initiate movements and the movements themselves are of lower amplitude.
  When more yields less: Understanding therapeutic gains according to lesion profile in chronic stroke aphasia.
  Dr A Woollams, Dr L Cloutman
Applications accepted all year round

Funding Type

PhD Type

Aphasia is a common consequence of stoke ultimately affecting one in five cases, with the most common residual difficulty being word finding difficulties, or anomia.
  Biologically-Plausible Continual Learning
  Dr K Chen
Applications accepted all year round

Funding Type

PhD Type

Continual learning (aka lifelong learning) refers to a problem on how a learning system learns multiple tasks in succession over the lifespan where later tasks do not degrade the performance of the system learned for the earlier tasks and, ideally, the system can leverage the knowledge learned in previous tasks to facilitate learning the new tasks better.
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