[BioNLP] PhD studentship in biomedical text mining, University of Manchester
Sophia.Ananiadou at manchester.ac.uk
Wed Dec 5 14:14:26 EST 2012
*PhD studentship in text mining approaches for understanding evolving concepts in heart failure*
Applications are invited for a 4 year studentship at the University of Manchester, providing full support for tuition fees, a minimum annual tax-free stipend of £13,590 and a conference/travel allowance. The project is due to commence October 2013 and is open to UK/EU nationals only due to the nature of the funding.
The studentship will be supervised by Prof. Garth Cooper in the Faculty of Medical and Human Sciences, Centre for Advanced Discovery and Experimental Therapeutics (http://www.manchesterbrc.org/OurFacilities/CADET.php). Co-supervision and text mining training will be provided by Prof. Sophia Ananiadou in the National Centre for Text Mining (http://www.nactem.ac.uk), School of Computer Science.
Development of new methods for the early detection of heart failure and monitoring of progression is hindered by the way we discover knowledge. Much of the evidence necessary to generate research hypotheses for developing comprehensive diagnostics, treatments and pharmacological interventions is found in textual sources.
It is critical to capture the context of such relations, i.e. the experimental species, tissue and disease contexts. Moreover, the suitability of a target must be determined through modelling bioprocesses from the molecular to the cellular and organism levels. These factors mean that the necessary information cannot be extracted and collated by manually reading the literature in the timeframe needed in clinical trial development and related drug discovery projects. Moreover, progression of our understanding has led to the description of multiple paradigms of heart failure.
Prior to these advances, a large body of valid and relevant investigations has been generated stretching back many decades. Linking these investigations through evolving concepts to current understanding is a challenging proposition for which text mining is key.
This interdisciplinary study will demonstrate how text mining can exploit information regarding omics, evolution of biological understanding and several biological organisational levels to analyse patterns of heart failure via the literature. The research will demonstrate how text mining can advance research by generating novel hypotheses for the causality of heart failure, based on objective assessment of prior knowledge. This will be performed in the context of an evolving clinical trials programme.
Applicants should hold a minimum upper-second honours degree (or equivalent) in computer science, bioinformatics, biology or biochemistry related subject. A Masters qualification in computing would be an advantage as would previous experience of natural language processing, text mining and applying computational techniques to biomedical areas.
Please direct applications in the following format to Professor Garth Cooper (garth.cooper at manchester.ac.uk) and Professor Sophia Ananiadou (sophia.ananiadou at manchester.ac.uk).
• Academic CV
• Official academic transcripts
• Contact details for two suitable referees
• A personal statement (750 words maximum) outlining your suitability for the study, what you hope to achieve from the PhD and your research experience to date.
Any enquiries relating to the project and/or suitability should be directed to Professors Cooper and Ananiadou.
Applications are invited up to and including Monday 7 January 2013.
Professor Sophia Ananiadou, School of Computer Science,
Director, National Centre for Text Mining
Manchester Institute of Biotechnology
University of Manchester
131 Princess Street, M1 7DN
sophia.ananiadou at manchester.ac.uk
tel: +44 (0)161 306 3092
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