Research Associate: Mathematical biologist/ecologist to develop the ‘Digital Microbiome’ for microbiome optimisation in agriculture

Imperial College London

Job description
Job summary

The Pawar Lab at the Silwood Park Campus of Imperial College London is seeking a mathematical / theoretical ecologist to lead the development of the Digital Microbiome towards optimising microbiomes to suppress the fungus Gaeumannomyces tritci which causes the take-all in wheat (T. aestivum).  This project, a collaboration between the Pawar, Waring , Ransome , Graystock and Bell labs, aims to find a new approach to supress this disease, which causes between 5-50% loss of production globally of one of the world’s most important staple crops.

The project has two overarching goals: 1) to develop a lab-to-field pipeline for bacterial microbiome optimization in arable soils to suppress G. tritci in the wheat rhizosphere; and 2) to advance our fundamental understanding of microbiome (AKA microbial community) dynamics in complex environments. Through directed artificial community-level selection guided by theory, we will develop soil microbiomes that suppress the take-all disease in greenhouse settings. Subsequent field trials will be aimed at not only identifying optimal protocols for inoculum delivery, but also to enhance our fundamental understanding of community assembly processes in the wheat rhizosphere.

You will be part of an inter-disciplinary project team of four postdocs and two research assistants across the four other labs, as well as the Digital Microbiome software development team.  In addition, you will also have the opportunity to collaborate with and co-supervise PhD, Masters, and Undergraduate students across the 5 labs, whose projects will be directly or indirectly linked to this project. The Digital Microbiome Project is a collaboration between the Patil lab at University of Cambridge and the Harcombe Lab at the University of Minnesota. It is a Julia-language based software package that provides a pipeline that links AI-powered Genome-Scale modelling (GEMs) and ecological theory to allow trait-based optimisation (AKA engineering) of microbiomes for specific applied scenarios.

You will also be provided the resources to advance your own career along your desired path, through mentorship, professional development opportunities, and opportunities to develop collaborations that extend beyond the core group.  Additionally, you will have the opportunity to connect directly with farmers and other local stakeholders who are collaborating with our research group, including Rothamsted Research and CABI .

Duties and responsibilities

Your role will be to develop testable theoretical predictions for the suppression efficacy of different microbiome consortia as well as the stability of these consortia to biotic (species invasions) and abiotic (temperature, nutrients, pH) perturbations, as well as the timing of microbiome inoculations with respect to the wheat life cycle. Specifically, the goal will be to use a trait-based approach to identify general bacterial community-scale metabolic network properties through a merger of ecological and metabolic network theories. This will enable reliable “recipes” to engineer compositionally-different but functionally-equivalent microbiomes that can be used to inoculate the soil to suppress the pathogen. Model improvement will be accelerated through feedback between the modelling and lab-to-field experimental components of the project. You will therefore be expected to interact frequently with your colleagues in the laboratory, in the field, and through regular group meetings. Thus, as such, you will play a key role in the design of the lab-to-field experiments carried out by the rest of the team. By working closely together, this team has the potential to significantly advance our capacity to engineer and manage complex microbiomes to improve the sustainability of agriculture. You will also be expected to communicate the findings of your research through conference presentations and scientific publications.

Essential requirements

Essential criteria:

  • Hold a PhD (or equivalent) in mathematical biology, a related field or a closely related discipline

  • Excellent scientific communication skills, as evidenced by presentations at scientific conferences and publications in peer-reviewed journals
  • Evidence of effective collaborative work in a team environment
  • Experience with developing mathematical theory for understanding and predicting the dynamics of complex ecological systems (and in particular, microbiomes / microbial communities).
  • Experience with programming in at least two different modern object-oriented programming languages for efficient numerical computing (e.g., Julia, C++, or Python)
  • Experience with the management/organisation of large datasets and analysis using Python or R

Desirable criteria:

  • Experience working with pipelines for the analysis of ‘Omics data
  • Experience in constructing genome-scale metabolic models and flux-balance analysis

Further information

*Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant within the salary range £40,694 – £43,888 per annum.

Please note this position is available full time, fixed term for 3 years.

Applicants should provide a CV and a cover letter (two pages maximum) explaining their qualifications for the role.

Long-listed candidates will be contacted to complete a Belbin Profile (a free login will be provided) and a short ‘challenge question’ directly relevant to the role. Please note this is a team activity that will help with outlining development opportunities it won’t be a decision making tool.

We anticipate holding interviews for these candidates in late November.

Should you require any further details on the role please contact Samraat Pawar at [email protected] with ‘Green Microbiome PDRA’ in the subject line

The College is currently trialling a Work Location Framework. Hybrid working may be considered for this role and the role holder may be expected to work 60% or more of their time onsite, with 40% the minimum time spent onsite. The opportunity for hybrid working will be discussed at interview.

The College is a proud signatory to the San-Francisco Declaration on Research Assessment (DORA),which means that in hiring and promotion decisions, we evaluate applicants on the quality of their work, not the journal impact factor where it is published. For more information, see

The College believes that the use of animals in research is vital to improve human and animal health and welfare. Animals may only be used in research programmes where their use is shown to be necessary for developing new treatments and making medical advances. Imperial is committed to ensuring that, in cases where this research is deemed essential, all animals in the College’s care are treated with full respect, and that all staff involved with this work show due consideration at every level. /

We are committed to equality of opportunity, to eliminating discrimination and to creating an inclusive working environment for all. We therefore encourage candidates to apply irrespective of age, disability, marriage or civil partnership status, pregnancy or maternity, race, religion and belief, gender reassignment, sex, or sexual orientation. We are an Athena SWAN Silver Award winner, a Disability Confident Leader and a Stonewall Diversity Champion


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