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Research Scientist in Data Integration and Network Analysis

vor 2 Monaten


Dübendorf, Zürich, Schweiz eawag Vollzeit

Project Overview

Characterizing diverse chemical impacts on human and non-human organisms is a fundamental challenge in toxicology. Furthermore, gene-environment interactions may lead to different responses within the same species. Emerging computational methods, such as multi-level data integration and adverse outcome pathway (AOP) frameworks, represent opportunities to expand understanding of chemical impacts on different species and fill data gaps. These approaches may also provide opportunities for cross-species extrapolation of toxicity mechanisms.

Main Responsibilities

The successful candidate will lead a multi-source, multi-level data integration project. This project will involve forming networks of chemical toxicity mechanisms from molecular initiating events to adverse outcomes following the AOP framework. Key tasks include:

  • Data mining and web scraping
  • Harmonization of disparate data sources using diverse ontologies
  • Statistical analysis of resulting networks/linkages
  • Machine learning integration (if applicable)

This project will involve working with and integrating diverse data types, managing big data files, data visualization, and analyzing exploratory data linkages. This position is purely computational and is suitable for an individual who enjoys programming.

Requirements

A candidate for this project should have a Master's degree in environmental sciences, toxicology, bioinformatics, or a similar field. Essential experience includes programming (R or Python preferred). Experience with cloud computing and statistics would be beneficial, and knowledge in genetics would be an additional asset. A solid work ethic, mature teamwork attitude, and good English skills are essential.