About the Project
Biological research is undergoing a data revolution, where huge amounts of data are being generated every day. This is happening alongside increasing demands from funders and publishers to make these data available. Making data Findable, Accessible, Interoperable, and Reusable (FAIR) requires a great deal of a researcher’s effort to ensure that their data is described well enough so that others can search for and reuse it. Although more and more metadata standards are being produced to help researchers describe their data, the use of these standards is not widespread or easy. Biological data needs to be liberated
This project will give the applicant an exciting opportunity to address the problem of badly-described life science datasets by developing new machine learning algorithms to automate the annotation of life science data with ontology terms. This project aims to develop modern computational methods to help biologists to better describe their data. This will hopefully improve the quality of data, allowing other researchers to access FAIR data more easily, and with a greater amount of metadata that can power meaningful data integration.
The student will learn a wide variety of scientific approaches and methodologies to Machine Learning, data management, ontologies, and community software development. No prior Machine Learning experience is necessary, but we are looking for a highly motivated applicant who has strong interest in computer science and would enjoy working with large datasets on state-of-the-art high-performance computing environments, and with the wider ontology community. We welcome applicants from all backgrounds, particularly those from under-represented groups, to join a diverse, inclusive, and friendly group of computational researchers.
This project has been shortlisted for funding by the Norwich Biosciences Doctoral Training Partnership (NRPDTP). Shortlisted applicants will be interviewed as part of the studentship competition. Candidates will be interviewed on either the 8th, 9th or 10th January 2019.
The NRP DTP offers postgraduates the opportunity to undertake a 4-year research project whilst enhancing professional development and research skills through a comprehensive training programme. You will join a vibrant community of world-leading researchers. All NRPDTP students undertake a three-month professional internship (PIPS) during their study. The internship offers exciting and invaluable work experience designed to enhance professional development. Full support and advice will be provided by our Professional Internship team. Students with, or expecting to attain, at least an upper second-class honours degree, or equivalent, are invited to apply.
For further information and to apply, please visit our website: www.biodtp.norwichresearchpark.ac.uk
Funding Notes
For funding eligibility guidance, please visit our website: http://biodtp.norwichresearchpark.ac.uk/how-to-apply/funding-and-eligibility. Full Studentships cover a stipend (UKRI rate: £14,777pa – 2018/9), research costs and tuition fees at UK/EU rate and are available to UK and EU students who meet the UK residency requirements.
Students from EU countries who do not meet the UK residency requirements may be eligible for a fees-only award. Students in receipt of a fees-only award will be eligible for a maintenance stipend awarded by the NRPDTP Bioscience Doctoral Scholarships. To be eligible students must meet the EU residency requirements.