PhD in Statistical modelling of disease progression in Spinal Muscular Atrophy and Duchenne Muscular Dystrophy
A 3-year PhD Studentship is available within the Dubowitz Neuromuscular Centre, UCL GOS Institute of Child Health under the supervision of Professor Francesco Muntoni, Dr Giovanni Baranello and Ms Deborah Ridout.
Full Project Description - see https://www.ucl.ac.uk/child-health/study/funding-and-studentships/phd-studentships/phd-developmental-neuroscience/phd-funded
The project is suitable for applicants with an MSc in statistics or from a clinical neuroscience background with strong 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 studentship includes 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 (GOSHCC) and additionally funding can be available for advanced skills training, including conference attendance and travel. The student will also benefit from the biostatistical networks in place within UCL and GOSH ICH.
To apply, please send a CV including the contact details of two professional referees, and a covering letter explaining your reasons for applying for this studentship, giving details of any relevant experience. The application should be sent to Janet Nicholas, Programme Administrator, Developmental Neurosciences (This email address is being protected from spambots. You need JavaScript enabled to view it.). Enquiries regarding the PhD can be made direct to Dr Giovanni Baranello (This email address is being protected from spambots. You need JavaScript enabled to view it.) and Ms Deborah Ridout (This email address is being protected from spambots. You need JavaScript enabled to view it.).
Deadline for receipt of applications: Friday 29th November 2019
