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Defining the genetic causes of neonatal and early onset diabetes, Biological and Medical Sciences PhD Funded 4160


   Medical School

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  Dr Elisa De Franco, Dr S Flanagan, Dr Matthew Johnson  No more applications being accepted  Funded PhD Project (European/UK Students Only)

Exeter United Kingdom Applied Mathematics Bioinformatics Cell Biology Data Analysis Endocrinology Genetics Medical Statistics Molecular Biology

About the Project

This exciting fully funded PhD project will use next generation sequencing technologies to define the genetic basis of diabetes in neonates and infants.

Neonatal diabetes is diagnosed before the age of 6 months and is most commonly caused by mutations in a single gene. Identifying the genetic causes of neonatal diabetes has the unique potential to uncover the pathways which are essential for the production of insulin in humans and can result in improved therapy for these children.

The student will analyse genome sequencing and targeted next generation sequencing data from children affected with diabetes who are very likely to have a genetic mutation causing their condition. The student will use bioinformatic approaches to filter the variants and carry out genetic interpretation of the results to highlight the most likely causative variants. The analysis is very likely to result in the identification of novel genetic causes of disease and the student will replicate the novel genetic findings by screening the rest of the Exeter neonatal and early onset diabetes cohort (the largest in the world) and analysing genomic data from large cohorts such as the 100,000 genomes project and Genes and Health to define the disease spectrum.

The results of these studies will provide a diagnosis for families with a rare disease and will offer important insights into which genes regulate development and function of beta-cells. This new knowledge could identify novel biological pathways and therapeutic targets important for type 1 and type 2 diabetes.

This studentship offers a fantastic opportunity for a highly motivated individual to join a growing, interdisciplinary team of laboratory scientists, computer scientists and clinicians working on a broad range of diabetes-related research within Exeter. Whilst in Exeter, the successful applicant will be fully supported to develop computational and molecular genomics skills, whilst focussing on clinically relevant questions which will impact the lives of people living with disorders of insulin secretion. Developing these multi-disciplinary skills will allow the student to bridge-the-gap between large-scale data analysis and clinical impact, acting as a springboard for a successful career in diabetes research.

Please contact Dr Elisa De Franco informally for more details by email [Email Address Removed]                                 

This award provides annual funding to cover Home tuition fees and a tax-free stipend. For students who pay Home tuition fees the award will cover the tuition fees in full, plus at least £15,609 per year tax-free stipend. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee and no stipend.


Funding Notes

This award provides annual funding to cover Home tuition fees and a tax-free stipend. For students who pay Home tuition fees the award will cover the tuition fees in full, plus at least £15,609 per year tax-free stipend. Students who pay international tuition fees are eligible to apply, but should note that the award will only provide payment for part of the international tuition fee and no stipend.

References

The names of two referees familiar with your academic work are required. You are not required to obtain references yourself. We will request references directly from your referees if you are shortlisted.