Qualification Type: | PhD |
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Location: | Exeter |
Funding for: | UK Students, EU Students, International Students |
Funding amount: | £18,662 |
Hours: | Full Time, Part Time |
Placed On: | 5th September 2023 |
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Closes: | 1st November 2023 |
Reference: | 4846 |
The GW4 BioMed2 MRC DTP is offering up to 22 funded studentships across a range of biomedical disciplines, with a start date of October 2024.
These four-year studentships provide funding for fees and stipend at the rate set by the UK Research Councils, as well as other research training and support costs, and are available to UK and International students.
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 38 students over 2 cohorts in its second phase.
The 80 projects available for application, are aligned to the following themes;
Applications open on 4nd September 2023 and close at 5.00pm on 1st November 2023.
Studentships will be 4 years full time. Part time study is also available.
Project Information Research Theme:
Neuroscience & Mental Health
Summary:
Breakthroughs in genetics have identified specific CNVs that substantially increase risk for schizophrenia. These CNVs impact NMDA & GABAA receptors, but how this disrupts cortical function is unknown. You will develop computational models that capture changes in NMDA and GABA receptor dynamics in CNV carriers. These models will be applied to existing neuroimaging (MEG) and cognitive data to make novel insights connecting genetics to brain function and cognition.
Description:
Recent progress in understanding the genetics of schizophrenia has identified that specific rare but highly penetrant copy number variants (CNVs, deletions or duplications of segments of DNA) are associated with substantially increased risk for the condition. Pathway analyses have shown that these schizophrenia-associated CNVs have convergent impacts on synaptic genes, particularly those involved in the NMDA receptor complex, associated post-synaptic density and selected GABAA receptor complexes.
Brain imaging using magnetoencephalography (MEG) provides a means to explore the neural basis of convergent phenotypic effects in carriers of CNVs. Importantly, MEG signals are generated and modulated by synaptic coupling and dynamics in cortical columns, which when modelled, allow inference on changes at the synapse from non-invasive data.
You will work largely with existing MEG data to build and refine cortical models that will link the downstream effects of schizophrenia-associated CNVs to changes in the MEG signals from CNV carrying individuals. This work will involve training in brain imaging analyses and mathematical dynamical systems modelling as well gaining a broad background understanding of clinical neuroscience, neuroimaging, pharmacology, genetics and computational modelling.
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