Integrative multi-omics approaches for exploring host-microbime interaction and biomarker identification

Apply and key information

This project is funded by:

BBSRC/UKRI Doctoral Landscape Award

Summary

The intricate relationship between the host and its microbiome plays a critical role in health and disease. Microorganisms interact with the host’s immune system, metabolism, and physiology. In human, imbalance in the microbiome, has been implicated in various diseases, including diabetes, obesity, and cancer. In cattle, microbiomes have impact on productivity and methane emissions. Despite advances in metagenomics and microbiome research, the intricate molecular interplay between host and microbiome remains poorly understood, for example, the diet–microbiota–host interactions.

This project aims to develop an innovative AI-based multi-omics integration framework for comprehensive analysis of the relationships between microbiome, host and environment and their causal role in biological processes by addressing the following key questions:
1. What is the impact of the microbiome and its functional activities on biological process?
2. How does the interplay between the microbiome and the host at a genetic level influence traits such as metabolism and gene expression?
3. Can artificial intelligence and machine learning provide insights and potential strategies to manipulate the microbiome-trait connections to achieve desired outcomes?

A computational pipeline will be developed for integrating host and microbiome multi-omics datasets. Algorithms will be developed for the identification of biomarkers for specific traits/diseases using integrative analysis, which can be applied to either human health and/or animal science.

This studentship will benefit from a multidisciplinary supervision team – computer scientists, biologist and biomedical scientist. The successful candidate will be based at AIRC UU, and will be working with NICHE at UU and IGFS, QUB. Furthermore, the successful candidate will be invited to visit Agri-Food and BioSciences Institute.

The School of Computing at Ulster University holds Athena Swan Bronze Award since 2016 and is committed to promote and advance gender equality in Higher Education. We particularly welcome female applicants,as they are under represented within the school.

This project is a 4-year PhD project with enhanced training and 3+ month placement, which is fully funded by UKRI BBSRC through the NI Landscape Partnership in AI for Bioscience (NILAB) Programme, delivered by Queen’s University Belfast and Ulster University. Details of the enhanced training will be available later at qub.ac.uk/nilab/. NILAB aims to bridge the gap between biology and artificial intelligence to accelerate bioscience discovery and foster effective collaboration between academia, industrial partners, and government bodies. NILAB’s mission is to train the next generation of researchers to develop and use AI to uncover the rules of life, addressing challenges in human health, animal welfare, and sustainable food systems.

This project is open to both home and international applicants on a competitive basis.

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.

Clearly defined research proposal detailing background, research questions, aims and methodology

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%
For VCRS Awards, Masters at 75%
Experience using research methods or other approaches relevant to the subject domain
Work experience relevant to the proposed project
Publications - peer-reviewed
Experience of presentation of research findings

Equal Opportunities

The University is an equal opportunities employer and welcomes applicants from all sections of the community, particularly from those with disabilities.

Appointment will be made on merit.

Funding and eligibility

This project is funded by:

BBSRC/UKRI Doctoral Landscape Award

This fully funded PhD scholarship will cover tuition fees and provide a maintenance allowance of £20,780 per annum for four years* (subject to satisfactory academic performance). A Research Training Support Grant (RTSG) of £5000 per annum is also available.

This scholarship is open to applicants worldwide, regardless of residency or domicile.

Applicants who already hold a doctoral degree or who have been registered on a programme of research leading to the award of a doctoral degree on a full-time basis for more than one year (or part-time equivalent) are NOT eligible to apply for an award.

*Part time PhD scholarships are available, based on 0.5 of the full time rate.

Due consideration should be given to financing your studies.