Current Opportunities
We have three projects available for commencement in October 2013. Subject to confirmation of eligibility, successful students will receive a full 3 year studentship including a generous monthly stipend, travel and training grants and University of Cambridge fees.
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Integrative statistical methods for discovering the genetic basis of rare diseases
Supervisor- Ernest Turro (University of Cambridge Computational Biology Group)
Co-Supervisors: Sylvia Richardson (BSU) and Willem Ouwehand (Department of Haematology)
We are seeking a PhD candidate to help develop novel methodologies for inferring the genetic basis of various rare disorders. The power of methods to find such associations without exploiting prior knowledge is limited to very large, clear-cut effects. However, thanks to a recent expansion in knowledge relating to the underlying regulatory networks active in different cell types (e.g. as a result of the ENCODE project), there is now an opportunity to exploit regulatory datasets to uncover previously elusive causes of disease. We are seeking a PhD fellow who is interested in developing novel statistical methodologies to tackle these problems. The ideal candidate is statistically minded but also has a good grasp of implementing algorithms in software and applying them to very large datasets. The successful candidate will have support from clinicians, biologists, bioinformaticians and biostatisticians by working jointly with members from the Department of Haematology and the MRC Biostatistics Unit.
About the Ouwehand group in the Department of Haematology: Our research focuses on the biology, genomics and genetics of platelets and their precursor cell- the megakaryocyte. The team comprises a wide range of research skills covering stem cell biology (including induced pluripotent stem cells), studies in model organisms, clinical data management and LIMS, computational genomics, and statistical genetics. We are expanding our computational team to advance exciting new enterprises. We are exploiting exome and whole-genome sequencing to identify the genetic basis of various rare disorders with relevance to cardiovascular diseases. We are also undertaking functional genomic studies through integration of gene expression and epigenomic data from haematopoietic cells within the Blueprint consortium. Furthermore we are developing clinical diagnostics using next-generation sequencing (NGS).
About the MRC Biostatistics Unit: The MRC Biostatistics Unit, located in Cambridge, was founded in 1913-14. Its aims are to advance understanding of the cause, natural history and treatment of disease, and to evaluate public health strategies, through the development of statistical methods and their application to the design, analysis and interpretation of biomedical studies. The Unit aims to maintain a balance between methodological development and application. The most useful new methodology is stimulated by applied studies, because attention is then focused on real problems rather than artificial abstractions, but this can still lead to generic ideas that are transferable between application areas. In turn, the Unit's involvement in applied studies is stimulated and enhanced by links to its methodological research programmes
Candidate Eligibility for this project: Only those candidates who would be considered Home/ EU students by the University of Cambridge are eligible to apply for this project due to funding constraints. Please see the University of Cambridge fee status webpage for details. Please note- applications from ineligible candidates will not be considered.
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Adaptive designs for telehealth trials
Supervisors: James Wason and Rob Blake (Philips Research Cambridge)
Telehealth products allow delivery of health-related services and information through telecommunications technology. Telehealth is a rapidly growing field due to improved technology and pressure on healthcare providers to reduce costs. Before release of a telehealth device, extensive trials must take place to prove it provides a safe and effective alternative to traditional care. The aim of this project is to develop and apply innovative statistical techniques, primarily adaptive designs, to trials of telehealth devices.
The main motivating example for this project is a new smartphone-like device, developed by Philips Research, for monitoring symptoms in patients undergoing chemotherapy. Its aim is to allow early identification of treatment-related toxicities that could potentially seriously harm the patient or affect the chemotherapy regimen applied, whilst minimising unnecessary hospital visits. A trial is currently being planned to assess this device in terms of whether it correctly classifies patients as requiring or not requiring hospitalisation. The sample size recruited is traditionally chosen so that the power of the trial is some pre-specified level, but the actual power depends on parameters for which there is little information on before the trial, such as the sensitivity and specificity. This can make choosing a suitable sample size difficult, and may result in a trial with little hope of recommending a genuinely effective device, or an overly expensive trial with too many patients. In this case adaptive designs, such as sample-size re-estimation designs, are very useful. They allow changes to be made to the planned sample size during the trial based on information gathered during the trial. In addition, adaptive designs can be used to allow data-dependent changes to be made to the device itself during the trial.
There has been a lot of research done on adaptive designs in traditional clinical trials, including several publications by scientists in the MRC Biostatistics Unit. However, there is little on trials evaluating diagnostic tests, such as a telehealth device, in which the data takes very different forms compared to traditional clinical trials. Research done in this project will be very useful in a wide variety of disease areas. The student will work on developing new statistical methods for applying adaptive trial designs to diagnostic test studies. As well as methodological work, they will also be involved in designing real-life trials of telehealth products being developed by Philips. The project will involve working both at the MRC Biostatistics Unit and Philips Research Cambridge's offices and will involve collaborating with a wide variety of people in academia and industry.
The project will be supervised by James Wason, a senior investigator statistician at the MRC Biostatistics unit, who has significant experience in the field of adaptive designs, and Rob Blake, a senior scientist at Philips Research Cambridge who leads the company's telehealth development in oncology and respiratory illnesses.
Candidate Eligibility for this project: The project is funded by an EPSRC industrial CASE award and as such is subject to strict EPSRC eligibility criteria. EPSRC iCASE awards come with an enhanced stipend and successful students will be funded for 3.5 years. Please note- applications from ineligible candidates will not be considered.
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Estimating HIV incidence from different sources of surveillance data
Supervisor- Daniela De Angelis
Co-Supervisors: Andrew Copas (University College London), Anne Presanis (MRC BSU) and Valerie Delpech (Public Health England)
With an estimated 96,000 (95%CI 90,800 – 102,500) prevalent infections in 2011 in the United Kingdom (UK), 22,600 (95%CI 17,600 – 29,000) of which are estimated to be undiagnosed, and evidence of sustained transmission in men who have sex with men (Presanis et al 2011b, Birrell et al 2012a,b), HIV still poses important and ongoing challenges to public health in this country. The evidence for sustained transmission suggests that current public health practices, whether around testing or treatment eligibility, need new thinking.
Methods for HIV incidence estimation, which assess the current level of transmission and allow identification and quantification of the drivers of transmission, are crucial to inform improved prevention and intervention efforts.
Powerful surveillance systems exist to monitor HIV infection in the UK, generating invaluable data not yet fully utilised. This project aims to
1) further develop current methods for estimating HIV incidence from surveillance data, in order to create a tool for the routine estimation of incidence;
2) explore and develop novel methods for estimating HIV incidence from newly available data sources, including;
a) results from assay-based tests for recent infection among newly diagnosed infections;
b) information on repeat testers at STI clinics;
c) molecular information among newly diagnosed infections;
3) investigate the possibility of merging different approaches, to make the best possible use of all available information.
Candidate Eligibility for this project: Only those candidates who would be considered Home/ EU students by the University of Cambridge are eligible to apply for this project due to funding constraints. Please see the University of Cambridge fee status webpage for details. Please note- applications from ineligible candidates will not be considered.
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How to apply
Eligible candidates are asked to provide the following;
a. a curriculum vitae
b. a letter of application detailing the project of interest, motivation to apply and suitability for the project of choice
c. a list of all statistics course taken
d. names and contact details for 2 academic referees who can be contacted prior to interview
to be sent to [log in to unmask] by Friday 24th May 2013.
Interviews will be held the week commencing the 3rd June (TBC).
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Please note: we are currently only accepting applications from UK or EU candidates only. All other candidates should check our website in the Autumn when we will begin recruitment for October 2014 entry.
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