PhD Studentship: Data Analytics to Disentangle Molecular Level Interactions in Microbiomes

This 3.5 year PhD is fully funded by The Department of Chemistry. Tuition fees will be paid and you will receive a tax free stipend set at the UKRI rate (£19,237 for 2024/25). The start date is September 2024. This funding is for UK students and those with settled status.

We have an exciting opportunity for a PhD student with an interest in data analytics to join our team working on the BBSRC funded SLoLa project “Rules of life in CO2-driven microbial communities: microbiome engineering for a Net Zero future”.
The project will study how the complex mix of microorganisms in a microbiome interact with each other to understand why these stable microbial communities form and how we can engineer a microbiome to utilize CO2 better as a carbon source to capture CO2 and generate useful organic products. To establish the dynamics of the interactions between the different organisms in the microbial community we will be using a range of mass spectrometric techniques, including proteomics and metabolomics and stable isotope labelling and flux analysis on some of the latest generation equipment. These methods generate large amounts of raw data, and methods to improve effective and efficient data extraction, analysis and processing are needed.

This studentship will be based in the world-renowned Manchester Institute for Biotechnology at the University of Manchester working under the supervision of Professors Pitt, Breitling and Cameron. This studentship would suit someone interested in generating new methods and pipelines for data extraction and processing of mass spectrometry data. This is a key role that sits between data collection and bioinformatics and data modelling This will require someone with an interest in data analysis and experience of scripting. The role will require working closely with the data generation and modelling teams, and there will be an opportunity to perform some data collection if interested.

Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline.

Please contact the main supervisor, Prof Andrew Pitt, before you apply: andrew.pitt@manchester.ac.uk

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