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Imaging the local accumulation and clearance of protein aggregates in the extracellular space of the brain in Alzheimer’s disease models.

  • Full or part time

    Prof F Gunn-Moore
  • Application Deadline
    Monday, June 15, 2020
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Small aggregates of misfolded proteins are thought to be the main cause for cellular death in a wide variety of neurodegenerative diseases. A large fraction of these aggregates (particularly in the case of amyloid beta) are present in the extracellular space, which despite being almost 20% of the brain volume, is relatively unexplored due to the lack of techniques that can work at the right spatial resolution in physiological conditions. Taking advantage of the techniques we have recently developed; the PhD project aims to study the way protein aggregates accumulate and are cleared from this convoluted space. This will have deep consequences in the way we understand the spreading of neurodegeneration along the brain, particularly during early stages of the disease.

We are looking for an enthusiastic PhD student with a strong background in either physical or biological sciences, willing to work in an interdisciplinary environment studying the brain at the single-molecule level. Experience in biophysics and/or neurosciences will be advantageous.

Applicants may contact the PI by email () for informal enquiries prior to submitting the application.

Funding Notes

This position is fully funded (for 3.5 years) by Alzheimer’s Society for UK and ERC Starting Grant “BrainNanoFlow”.

Applicants should hold or expect to gain at least a 2:1 Bachelor Degree or equivalent in related subject area. Due to the interdisciplinary nature of the project, applicants may have background studies in either biological or physical sciences.


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How good is research at University of St Andrews in Biological Sciences?

FTE Category A staff submitted: 50.45

Research output data provided by the Research Excellence Framework (REF)

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