Applications are invited for a postdoctoral research fellow in Biomedical Text Mining at the National Centre for Text Mining (NaCTeM), School of Computer Science, University of Manchester.

The objective of this BBSRC funded post in collaboration with Unilever is to conduct research into extracting complex information from the scientific literature to support metabolic pathway curation using text mining methods.

The project will involve close collaboration with a team of experts focusing on metabolomics and cheminformatics.
More information about the project: http://www.nactem.ac.uk/empathy/

Research Environment
The National Centre for Text Mining (www.nactem.ac.uk<http://www.nactem.ac.uk/>) has been a leading centre for biomedical text mining since 2004, with areas of expertise in information extraction, terminology, text classification, text mining infrastructures and semantic search systems.
NaCTeM is located in the Manchester Institute of Biotechnology (www.mib.ac.uk<http://www.mib.ac.uk/>) and its staff belong to the 4th ranked Computer Science school in the UK (REF2014) which has been further assessed as having the “best environment in the UK for computer science and informatics research”.


University of Manchester

Qualifications and Experience:

Candidates should have a PhD in Computer Science with emphasis in Natural Language Processing/Text Mining; working experience in information extraction at large scale; excellent knowledge in developing and adapting algorithms for text mining systems; machine learning; experience in biomedical Text Mining; strong track record of high-quality papers in conferences such as ACL, EMNLP, etc., and in high quality journals; excellent programming skills; proven ability to develop independently research proposals.

Specific requirements:

Duration of post: until 31st March 2018 with possibility of extension

Informal enquries

Informal enquiries: Prof. Sophia Ananiadou (Sophia.ananiadou@manchester.ac.uk).

Educational level:

Ph. D.

How to apply:

Please mention NLP People as a source when applying


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