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Developmental Neuroscience: Statistical exploration and prediction of disease progression in Spinal Muscular Atrophy and Duchenne Muscular Dystrophy: implications for therapy


Project Description

A 3-year PhD Studentship is available within the Developmental Neuroscience Department – Dubowitz Neuromuscular Centre, UCL GOS Institute of Child Health under the supervision of Professor Francesco Muntoni, Dr Giovanni Baranello and Ms Deborah Ridout.

• Project Description – see https://www.ucl.ac.uk/child-health/study/funding-and-studentships/phd-studentships/developmental-neuroscience-statistical-exploration

The project would be suitable for a student with an MSc in biostatistics or for a student with a background in epidemiology or public health with strong statistical analytic skills.

Applicants should have or expect to receive a first class or upper second class honours degree and should be ordinarily resident in the UK or EU. Previous research experience working with large, complex data and the application of advanced statistical methods would be an advantage, but training in the techniques required for the research will be provided. The student will receive a stipend of £17,500 per annum as well as the cost of tuition fees at the UK/EU rate. Any additional overseas’ student fees must be paid by the student. The studentship is funded by the Great Ormond Street Hospital Charity (GOSHC).

To apply, please send a current CV including the contact details of two professional referees, and a covering letter explaining your reasons for applying for this studentship, and giving details of any relevant experience. The application should be sent to Janet Nicholas, Programme Administrator, Developmental Neurosciences (). Enquiries regarding the PhD can be made direct to Dr Giovanni Baranello () and Dr Deborah Ridout ().

Deadline for receipt of applications: Monday 16th September 2019
Interviews will take place during week beginning 14th or 21st October 2019

How good is research at University College London in Clinical Medicine?

FTE Category A staff submitted: 449.74

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

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