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Name of scholarship/program

Translating Protein Network Models into the Clinic using Machine Learning Algorithms

Important description
Understanding protein signalling networks at the molecular level is crucial to find new cures for diseases like cancer. Single molecule microscopy techniques have been developed and applied to study these interactions and unravel their fundamental biology. This challenging PhD project aims to remove a key data analysis bottleneck, where slow, manual work is needed to select results for modelling and interpretation. Machine learning algorithms will be developed to automatically learn from and encapsulate the human judgments currently needed to select data. These will be incorporated into our Bayesian analysis pipeline to enable full automation and exploitation of single molecule techniques in the clinical setting.

Project location: The PhD student will be based at the Research Complex at Harwell (http://www.findaphd.com/common/clickCount.aspx?theid=44715&type=75&url=http%3a%2f%2fwww.rc-harwell.ac.uk"" target=""_blank"" rel=""nofollow""> http://www.rc-harwell.ac.uk ). The PhD will be awarded by the Division of Cancer Studies at King’s College London. The student will be part of a large interdisciplinary team that includes physicists, mathematicians, molecular biologists, biochemists and microscopists and will benefit from day-to-day interactions with this team. The programme of work is part of a collaborative consortium led by Prof. Peter Parker (Kings College London) and Dr. Marisa Martin-Fernandez (Science and Technology Facilities Council), which also includes astronomers and engineers at Cambridge University. The PhD student will also benefit from regular interactions with the large team of scientists involved in the consortium.

The PhD student should have a numerical background. All shortlisted applicants will be interviewed by at least two academics. Applications are welcomed from European Union candidates.

Eligibility and other criteria
This research project has funding attached. Funding for this project is available to citizens of a number of European countries (including the UK). In most cases this will include all EU nationals. However full funding may not be available to all applicants and you should read the full department and project details for further information.

Application deadline
*19 May 2013

Additional information, and important URL

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