BERRYU18FMH Dietary polyphenols, neuro-inflammation and cognitive decline

Are you interested in how diet and lifestyle influence brain structure and function? We are looking for a computationally minded PhD candidate who can apply machine learning to investigate the factors underlying cognitive decline and dementia.

“What’s good for the heart is good for the brain” has become common wisdom in dementia prevention. Nonetheless, how cardiovascular risk factors, and interventions targeting them, impact brain health remains unclear. Amongst dietary constituents, work from our department and others has emphasised the beneficial cardio-metabolic effects of polyphenols (bioactive components found in foods such as berries, cocoa and tea). This project will utilise an existing dataset that includes measures of diet, lifestyle, brain structure/function (MRI), inflammation and cognition. You will apply cutting edge machine learning techniques to big data to identify new targets for preventing dementia and slowing cognitive decline. In addition, you will be given the opportunity to participate in applied laboratory research e.g. analysing blood samples to determine the association between inflammation and cognitive function.

We believe that curiosity, enthusiasm and a growth mind-set are the most important ingredients for success, although experience in statistics or computer science and biology would not hurt. If you would like to know more, take a look at our earlier work (1,2,3) and the works of others in this field (4,5) and see if this is the type of work interests you. I would be delighted to discuss this position further at [Email Address Removed].

For more information on the supervisor for this project, please go here: https://people.uea.ac.uk/en/persons/n-berry

Type of programme: PhD

Project start date: April 2019

Mode of study: Full time

Location: UEA - Bob Champion Research and Education Building

Entry requirements: Acceptable first degree - Epidemiology, computer science, mathematics, biostatistics, biomedical engineering.
The standard minimum entry requirement is 2:1.