Back to search results

PhD Studentship - Exploring the Feasibility and Efficacy of an Aerobic Exercise Intervention in Improving Dietary Self-regulation in Adolescents and Young Adults

University of Exeter - Psychology

Qualification Type: PhD
Location: Exeter
Funding for: UK Students, EU Students, International Students
Funding amount: £19,237
Hours: Full Time, Part Time
Placed On: 11th September 2024
Closes: 4th November 2024
Reference: 5267

About the GW4 BioMed2 Doctoral Training Partnership

The partnership brings together the Universities of Bath, Bristol, Cardiff (lead) and Exeter to develop the next generation of biomedical researchers. Students will have access to the combined research strengths, training expertise and resources of the four research-intensive universities, with opportunities to participate in interdisciplinary and 'team science'. The DTP already has over 90 studentships over 6 cohorts in its first phase, along with 58 students over 3 cohorts in its second phase.

Project Information

Research Theme: Neuroscience & Mental Health

Summary: During this exciting, fully-funded PhD, you will use machine learning to automatically classify the state of microglia (the brain’s specialised immune cells). This will involve combining mathematics, computer programming and artificial intelligence with real experimental data to develop both supervised and unsupervised methods to predict microglial state. You will have the opportunity to collaborate with researchers in Exeter, Bristol, Newcastle and Leeds. This work has significant potential applications throughout biology and medicine, including in drug discovery, cancer and neurodegenerative conditions such as motor neuron disease, Parkinson's disease and Alzheimer's disease.

Project Description: Background: Microglia are the resident immune cells of the brain. They adopt a wide range of phenotypes to control the brain’s immune response, including phagocytosing unwanted agents and releasing signalling chemicals to other cells in the brain. The scientific community has spent the last fifty years naively categorising microglial phenotype into just two types: M1 (inflammatory) and M2 (anti-inflammatory). However, recent work (including that by our collaborators) has led to the revolutionary idea that microglial state should instead be a “multidimensional concept”, with a spectrum of states. Importance: Determining how many states microglia can exist in, whether these states form a continuum and being able to predict microglial state is of fundamental medical importance. This is because microglia play a vital role in neurodegenerative disease (including motor neuron disease, Parkinson's disease and Alzheimer's disease) and cancer. Improved prediction of microglial state, particularly if this can be achieved from standard bright-field imaging, could revolutionise diagnosis of these conditions and provide a valuable tool in the search for treatments by, for example, aiding drug screening programmes. Machine learning: The vision is that microglial state could be predicted simply from cell shape. A human attempt to do this would be timeconsuming and would be affected by unconscious bias and human error. Instead, what is needed is an automatic computational method. This is precisely what machine learning can achieve. Preliminary results in our group show that microglia can be classified with high accuracy (>93%) even using single cells. The aim of this PhD is to improve this.

We value your feedback on the quality of our adverts. If you have a comment to make about the overall quality of this advert, or its categorisation then please send us your feedback
Advert information

Type / Role:

Subject Area(s):

Location(s):

PhD tools
 

PhD Alert Created

Job Alert Created

Your PhD alert has been successfully created for this search.

Your job alert has been successfully created for this search.

Ok Ok

PhD Alert Created

Job Alert Created

Your PhD alert has been successfully created for this search.

Your job alert has been successfully created for this search.

Manage your job alerts Manage your job alerts

Account Verification Missing

In order to create multiple job alerts, you must first verify your email address to complete your account creation

Request verification email Request verification email

jobs.ac.uk Account Required

In order to create multiple alerts, you must create a jobs.ac.uk jobseeker account

Create Account Create Account

Alert Creation Failed

Unfortunately, your account is currently blocked. Please login to unblock your account.

Email Address Blocked

We received a delivery failure message when attempting to send you an email and therefore your email address has been blocked. You will not receive job alerts until your email address is unblocked. To do so, please choose from one of the two options below.

Max Alerts Reached

A maximum of 5 Job Alerts can be created against your account. Please remove an existing alert in order to create this new Job Alert

Manage your job alerts Manage your job alerts

Creation Failed

Unfortunately, your alert was not created at this time. Please try again.

Ok Ok

Create PhD Alert

Create Job Alert

When you create this PhD alert we will email you a selection of PhDs matching your criteria.When you create this job alert we will email you a selection of jobs matching your criteria. Our Terms and Conditions and Privacy Policy apply to this service. Any personal data you provide in setting up this alert is processed in accordance with our Privacy Notice

Create PhD Alert

Create Job Alert

When you create this PhD alert we will email you a selection of PhDs matching your criteria.When you create this job alert we will email you a selection of jobs matching your criteria. Our Terms and Conditions and Privacy Policy apply to this service. Any personal data you provide in setting up this alert is processed in accordance with our Privacy Notice

 
 
 
More PhDs from University of Exeter

Show all PhDs for this organisation …

More PhDs like this
Join in and follow us

Browser Upgrade Recommended

jobs.ac.uk has been optimised for the latest browsers.

For the best user experience, we recommend viewing jobs.ac.uk on one of the following:

Google Chrome Firefox Microsoft Edge