Research Associate in Disease Modelling

Location: South Kensington Campus

Job Summary

This is an exceptional opportunity for an ambitious Research Associate to contribute to ground-breaking research with the potential to transform malaria control strategies and improve the health of communities in sub-Saharan Africa and beyond. Transmission Zero (https://www.transmissionzero.org/) is an international research programme with the mission to pioneer innovative genetic vector control tools for combatting malaria transmission in sub-Saharan Africa.

We are developing CRISPR/Cas9-based gene drive systems that are aimed at modifying vector populations by introducing transgenes that inhibit malaria transmission in wild Anopheles mosquito populations across Africa, thus aligning with global efforts to eliminate malaria. Successful candidates will play a crucial role in the validation of such gene drives by predicting the behaviour of these interventions at different scales using computational models.

Transmission Zero involves international partners including the Ifakara Health Institute and the National Institute of Medical Research in Tanzania, as well as the Swiss Tropical and Public Health Institute (https://www.transmissionzero.org/). During its seven years of operation, the programme has already achieved several important milestones, including the creation of Africa's first genetically modified mosquito for vector population modification using gene drives. Over the next three years, our primary objectives include expanding our portfolio of gene drives and antimalarial effectors, refining existing tools, and progressing toward gene drive field trials.

You will help to create computer models and tools that will facilitate investigation of the gene drive technologies being developed. The work will build on the EMOD family of existing agent-based models, which simulate mosquito populations across large areas of Africa (https://docs.idmod.org/models.html#emod). You will adapt these models to specific genetic constructs and locales and enhance the models with additional features to address new research questions. You will interrogate these models to gain insights on malaria transmission dynamics and how genetic control measures would impact transmission.

The role offers a unique opportunity to contribute to ground-breaking research with the potential to transform malaria control strategies and improve the health of communities in sub-Saharan Africa and beyond. If you have a passion for cutting-edge computational modelling, we encourage you to apply and be part of our dynamic team at Transmission Zero. 

Duties and responsibilities

• You will design and perform computational simulations to generate high-quality, publication-worthy data contributing to the advancement of the scientific programme and timely achievement of its various milestones and deliverables.
• You will contribute to development of the EMOD modelling framework and its gene drive module, calibrating ecological and epidemiological models using location-specific data and provide modelling input to field trial design and risk assessments.

Essential requirements

• You should hold, or be near completion of, a PhD in Computer Science or a relevant STEM subject (e.g. quantitative epidemiology, biology) or a closely related discipline, or equivalent research, industrial or commercial experience.
• Practical experience of working within a highly competitive research environment and a high level of expertise and experience in at least one programming language are essential. 

Further Information

The post is available full-time, fixed term until 31 December 2026. You will be based at the South Kensington Campus.

Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant.

Should you require any further details on the role please contact: Dr Nikolai Windbichler, n.windbichler@imperial.ac.uk or Professor George Christophides, g.christophides@imperial.ac.uk.

Closing Date: 04/07/2024

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