Eawag, the Swiss Federal Institute of Aquatic Science and Technology, is an internationally networked aquatic research institute within the ETH Domain (Swiss Federal Institutes of Technology). Eawag conducts research, education and expert consulting to achieve the dual goals of meeting direct human needs for water and maintaining the function and integrity of aquatic ecosystems.
The Department of Systems Analysis, Integrated Assessment and Modelling (Siam) is announcing a
The position is part of a project focused on the development of deep learning applications and sampling strategies to support in-situ monitoring tools for the study of phytoplankton dynamics in lakes.
We are looking for excellent candidates with a solid background in either machine learning, probability or statistical physics. Good communication skills, open mind and an interest to cross disciplinary boundaries are also appreciated, due to the close interaction with collaborators coming from different domains. The researcher will be expected to use computer vision methods to analyze camera images, to develop semi-supervised learning strategies for dataset creation, and to devise monitoring schemes for optimal sampling of field data. The researcher will be required code in Python and to manage jobs in a computer cluster.
Closing date is 31 March 2020, but the screening of applicants will begin on 1 March 2020. Your application should include a CV, a short motivation letter and the names and contact information of two references.
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.