This is an opportunity for an experienced and enthusiastic text analytics researcher to work on the SAVSNET project.
SAVSNET (Small Animal Veterinary Surveillance NETwork; www.savsnet.co.uk) collect health records in real-time from diagnostic laboratories (~80,000 tests/day) and veterinary practices (~5,000 consultation records/day) from across the UK. These data are being used to provide freely accessible disease information, and surveillance updates, as well as a growing portfolio of epidemiological research in health of pets in the UK.
SAVSNET have already developed a series of clinical text mining algorithms to extract clinical signs and parameters recorded in the veterinary clinical narrative.
The current project is funded by BBSRC to consolidate the existing and develop new text-mining algorithms that are able to identify key details and context of each patient’s visit in near-real time.
The main aim is to build production-level text mining tools to enhance data access by identifying mentions of problems, symptoms and prescriptions and map these to existing clinical coding structures. The project will involve designing, consolidating and implementing both rule-based and data-driven approaches, and their integration within the existing SAVSNET platform.
You should have or be about to obtain a PhD or equivalent in health informatics or computer science, with significant experience in processing textual data. Experience of rule-based and statistical methods for identification of key concepts (such as clinical problems, symptoms, etc.) is essential. Experience and enthusiasm for research focused on veterinary data is desirable.
You will also have a proven and consistent track record of productivity and software development, including recent research papers in health informatics and/or text analytics. For further information, please see the further particulars.
The position is based in the School of Computer Science at Manchester, but will also involve travel to and close collaboration with the SAVSNET team based in the Leahurst campus (near Liverpool). The post can also be part-time for the equivalent duration, and is available from March 1st 2017 (but a later start is possible).
The University of Manchester values a diverse workforce and welcomes applications from all sections of the community. We are committed to promoting equality and diversity, including promoting women’s careers in STEMM subjects (science, technology, engineering, mathematics and medicine) in higher education (the School of Computer Science has been awarded a Bronze SWAN Award for our commitment to the representation of women in the workplace). We particularly welcome applications from women for this post, but appointment will always be made on merit.
Please note that we are unable to respond to enquiries, accept CV's or applications from Recruitment Agencies
Enquiries about the vacancy, shortlisting and interviews:
Dr Goran Nenadic, Reader
Tel: 0161 275 4499
Tel: 01565 818 234
Date of external posting: Friday 17 February 2017
This vacancy will close for applications at midnight on the closing date.