PhD Study : Integrated big data analytics in microbial metagenomics

Summary

This is a 3.5 year studentship based at the School of Computing, Jordanstown, Ulster University, in collaboration with the Scotland’s Rural College (SRUC).  The project would suit a graduate with a Computer Science, Informatics and Bioinformatics background.

The overall aim of the project is to develop integrated big data analytics algorithms for microbial metagenomic analysis. Data used in this study are provided by SRUC. The algorithms will investigate and discover knowledge from the abundances of the rumen microbial community and microbial genes as well as their biological mechanisms to predict performance traits such as feed conversion efficiency, meat quality (Omega-3 fatty acids) and methane emissions in beef cattle. Outcome of this study can be used for genetic improvement programmes, nutritional interventions and precision farming to improve productivity, resource efficiency, economics, product quality with reduced environmental impact of animal production. The algorithms developed can be applied to other animal and even human microbial analysis. An advanced multiplex network-based approach which is capable to facilitate the crosstalk and interactions between different information sources including abundances of microbial community and microbial gene information will be developed. The pipeline will be provided as open source software so that its use will be widespread and improvement and adaption to specific analysis can be achieved easily after the end of the research project.

This project would suit someone with an interest in big data analytics and bioinformatics. Applicants should have or expect to obtain a minimum of an upper second class honours degree (or equivalent) in a relevant computer science or informatics subject area. Excellent numeracy and communication skills (both verbal and written) are required.

The studentship will be jointly supervised by Prof. Huiru(Jane) Zheng (Ulster), Prof. Rainer Roehe (SRUC), Dr. Haiying Wang (Ulster) and Prof Richard Dewhurst(SRUC). The student will be trained at Ulster University in machine learning, bioinformatics, and at SRUC in presently used metagenomic analysis, microbiology, genetics and nutrition.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

• First Class Honours (1st) Degree
• Masters at 70%

Funding and eligibility

This project is funded by:

• Scotland's Rural College

This 3.5 year of studentship will comprise tuition fees and a maintenance award of not less than £15,000 per annum. Applicants should hold ordinary UK/EU residence to be eligible for both fees and maintenance. Non-EU students would have to cover the difference between UK/EU tuition fees and the non-EU tuition fees.