Post Doctoral Research Assistant in Ecological and Mathematical Modelling

This is an externally-funded PDRA position supporting the UKRI/NERC Seedcorn Funding project “Developing a framework of key predictors of antimicrobial resistance emergence and transmission in Chilean wastewater”. You will work closely with an international team of researchers and stakeholder across multiple disciplines from leading institutions in the UK (University of Lincoln, University of Surrey, University of Leeds, UKCEH) and Chile (Universidad de Desarrollo and MICROB-R). You will use a system modelling approach to a) quantify available data, b) knowledge gaps and associated risks to c) develop a risk assessment framework to prevent and reduce the spread of environmental antimicrobial resistance (AMR).

Antimicrobial resistance (AMR) – the phenomenon whereby microorganisms that were previously treatable with antimicrobials become untreatable – is predicted to overtake cancer as the leading cause of death within the next two decades. The role that humans and livestock components play in AMR has received much attention and thus is broadly understood. In contrast, the environmental component of resistance lags behind, despite mounting evidence of its key role in the development, transmission and spread of AMR.

Within the Latin American region, Chile represents one of the leading countries in the control of antibiotic resistance, with one of the lowest mortality rates associated to AMR. In the Chilean National Action Plan on AMR, a key policy document tackling the country’s approach to this public health threat, self-reported progress on the implementation of the plan showed good progress in human, animal health, and agriculture, but no progress for the environmental sector.

The aim of this project is to fill this gap by launching a new international network — a UK-Chile collaboration using a systems approach to tackle antimicrobial resistance in the environment—involving a feasibility study and system modelling of environmental AMR in wastewater. You will use data on AMR in wastewater to tackle the environmental threat of AMR.

You will have a PhD (or close to completion) in modelling complex systems or a closely allied discipline along with experience in creating, writing, enhancing, and running code in R. You will have excellent communication skills with the ability to talk to different audiences, as you will be collaborating with a team of researchers across multiple disciplines both in the UK and overseas.

For questions and further information please contact Graziella Iossa at GIossa@lincoln.ac.uk.

You can find out more about working at Lincoln, and everything that we have to offer, at: 

https://www.lincoln.ac.uk/jobopportunities/

We strive for a diverse workforce with the very best employees and are committed to creating an inclusive environment for all. The University encourages applications from underrepresented groups inclusive of Black, Asian and other minoritised/marginalised ethnic groups, all gender identities and expressions from the LGBTQIA+ community, candidates with a disability, and those that practise different faiths and beliefs, to enhance our One Community where we strive to be kind, patient, and supportive of each other.

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