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PostDoc position to predict genetic susceptibility to chemicals in environmentally-relevant species

vor 2 Wochen


Dübendorf, Schweiz eawag Vollzeit
Project background:  Chemical pollution threatens biodiversity of ecosystems, yet we know little about different species’ genetic susceptibility to chemicals. Elucidating the relationship between chemical exposures and population genetics for diverse species is essential to protect genetic variability in ecosystems and determine an ecosystem’s resilience and adaptation potential following chemical exposure. However, lab- and field-based methods to assess chemical impacts on the genetics of populations are impossible to conduct for all combinations of chemicals and species. Therefore, computational methods are necessary to help characterize and predict genetic susceptibility to chemicals for different species in an ecosystem.
Project description: In this project, the postdoc will model the relationship between genetic susceptibility to chemicals and adverse outcomes in different species. This project involves curating and integrating diverse data sources related to, e.g., chemical toxicity, spatial chemical use, genetic variation, and species occurrence. Different approaches can be used to develop these methods, including data integration to build/characterize new data linkages, adverse outcome pathway (AOP)-based approaches, or gene-environment association methods. There is also room for development of new ideas and methods by the postdoc. As a starting point, this project will focus on pesticide-induced neurotoxicity for D. rerio and C. elegans before expanding the predictive models to less well-studied species. This postdoc position is purely computational and is for an individual who enjoys programming or is interested in further developing their programming skills. 
As a candidate for this project, you should have a PhD in environmental sciences, toxicology, bioinformatics, or a similar field. Experience in programming (R or Python preferred), geospatial analysis, and managing big data would be a benefit. Knowhow in genetics would be an additional asset. A strong work ethic, mature teamwork skills, and good English knowledge are essential.