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Multi-omics data fusion for better understanding of host-microbe interactions in health and disease

About This PhD Project

Project Description

"The rapid development and adoption of high-throughput, high resolution analytical technologies (e.g. genomics, transcriptomics, proteomics, metabolomics, metagenomics) has resulted in the generation of an avalanche of omics data. Integrating data generated by these multi-platform omics approaches are essential for system-wide molecular characterisation and better understanding of mechanisms affected by disease state. Furthermore, fusion of complementary datasets (e.g. metagenomics and metabolomics) enables functional insight into the role of the gut microbiota, and the impact of host-microbe interactions on host health.

This PhD comprises a fusion between different systems biology approaches, and will focus on the development of computational strategies such as network analysis, machine learning and neural networks, to integrate and analyse multi-omics data that has already been collected from existing studies. There may be scope to acquire data using a range of different analytical approaches (e.g. metagenomics, metatranscriptomics, metabolomics) as well during the studentship.

Enquiries are welcomed from self-funded students. There may be an opportunity for a funded position in the near future. Applicants should hold (or expect to hold by October 2018), a Masters postgraduate degree (or equivalent overseas qualification) in bioinformatics, biostatistics, physical sciences, or an equivalent field. Outstanding candidates possessing an appropriate undergraduate degree may also be considered.

For informal enquiries and application please contact the supervisors listed above. Applications should include a covering letter, full CV (stating your nationality) and contact details of two referees one of whom must be academic. Expected start date: 1st October 2018.

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