Postdoctoral research position for Machine Learning in Ecotoxicology

  • Eawag
  • Dübendorf, ZH, Switzerland
  • 03/04/2021
Full time Data Science Data Analytics Big Data Data Management Statistics

Job Description

The position is part of a project focused on the development of machine learning models for ecotoxicology, trained on pre-existing databases of in-vivo and in-vitro assays. The overarching goal is to assess whether in-vivo experiments can be at least partly replaced, and to identify trends of toxic sensitivity through different taxa. The scientist will provide ecotoxicological domain knowledge and closely collaborate with the data scientists in the team, and will be in charge of maintaining and developing an in-vitro database using in-house and publicly available (e.g. ToxCast) knowledge.
The interdisciplinary project is led by Kristin Schirmer (Utox) and
Marco Baity-Jesi (Siam) and will be pursued in close collaboration with experts from the Swiss Data Science Centre. The place of work will be at Eawag in Dübendorf.
We are looking for excellent candidates with a solid foundation in ecotoxicology and a keen interest to contribute to the development of alternatives to animal experimentation. Expertise in dealing with data bases and applying computational approaches are strong assets. Familiarity with programming is valued. Good communication skills, an open mind and appreciation for the opportunities arising from crossing disciplinary boundaries are also highly appreciated. The period of employment for this project is 24 months.
Eawag is
 a modern employer and offers an excellent working environment where staff can contribute their strengths, experience and ways of thinking. We promote gender equality and are committed to staff diversity and inclusion. The compatibility of career and family is of central importance to us. For more information about Eawag and our work conditions please consult and
Applications must be submitted by 16 April 2021
, and should include an application letter describing your interests and their relevance to this position, a CV (without picture), a list of publications, and the names and contact information for three references.
For further information, please contact Kristin Schirmer or Marco Baity-Jesi.
We look forward to receiving your application.
 Please send it through this webpage, any other way of applying will not be considered. A click on the button below will take you directly to the application form.