Departments: MRC Social, Genetic and Developmental Psychiatry Centre and Biostatistics
Starting: September 2013
We have funding from Janssen Pharmaceuticals , a company of Johnson & Johnson, for a four year PhD studentship in bioinformatics/biostatistics, to develop methods to identify novel biomarkers for disease progression in Alzheimer’s disease.
A major challenge in Alzheimer’s (AD), and other diseases, is to identify biomarkers that predict disease progression. The aim of this project is to evaluate and improve on a range of available methods (leading to novel and improved models) for valid and more reliable estimation of progression of AD and subsequent detection of biomarkers.
This PhD research will develop and assess approaches for building biomarker prediction models that have clinical utility. This presents an exciting opportunity to develop cutting edge tools for the analysis of clinical and omics data that will be applied to on-going studies. The student will have incredible opportunities to exploit data from patient records and large EU funded projects such as the European Medical Informatics Framework.
The project will be jointly supervised by Dr Richard Dobson and Dr Mizan Khondoker (KCL) in collaboration with Professor Simon Lovestone and colleagues at Janssen Pharmaceuticals (Johnson & Johnson). The student will be part of the Bioinformatics and Biostatistics group at the Institute of Psychiatry, KCL, a thriving research group with over twenty researchers, and may have the opportunity to spend time at Johnson & Johnson during the studentship.
See full information at : http://www.kcl.ac.uk/iop/research/pgr/phdstudentships/Janssen.aspx
The studentship includes home fees and a full maintenance stipend of approximately £16,500 per annum. Applicants should be UK/EU nationals and resident in the UK for three years prior to starting the PhD. Non-EU candidates can apply but would have to cover additional fees.
Applicants are expected to have obtained a good undergraduate degree (2:1) or above. Students should have an academic background in bioinformatics, mathematics or statistics, although those from a life sciences background with strong analytical skills are also encouraged to apply. Students should have the ability to work independently, with effective written and oral communication skills.