PhD Student position for Machine Learning in Ecological Forecasting
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Job Location:
Uster - Switzerland
Monthly Salary:
Not Disclosed
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
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
PhD Student position for Machine Learning in Ecological Forecasting
The position is part of a project focused on the development of machine learning models for plankton abundance prediction trained on a state-of-the-art dataset developed at Eawag. The project will focus on training nowcasting and forecasting models promoting rigorous machine learning practices and understanding the relevance of different sources of data and environmental conditions towards the predictability of the state of a plankton community.
The project is led by Marco Baity-Jesi(SIAM department) in collaboration with Francesco Pomati(ECO department) and with the Swiss Data Science Center. The place of work will be at Eawag in Dübendorf and the PhD will be part of the D-USYS department at ETHZ.
Skills that we appreciate for this position
Strong motivation towards using machine learning applied to ecology
Fostering a healthy environment around you
Proactivity in interacting with colleagues within and outside of the team
Creativity and good communication skills
Comfort training machine learning models (e.g. with PyTorch)
Clean coding and scripting practices
Comfort with time series analysis
Basic knowledge on differential equations
Comfortable with mathematical manipulation and with translating math into code
Knowledge in community ecology especially plankton ecology
Since the project is interdisciplinary we do not expect you to excel in all these aspects before you start. We value self-awareness: If you believe you lack some of these skills but the project excites you you might be the right person for us. We do not evaluate based on so-called merit. We look for the person who is the best match for this position.
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 submitted by 5 November 2025 will be granted full consideration. These should include an application letter describing your interests and their relevance to this position a CV (without picture) and the names and contact information for two references.
For further information please contact 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.
The project is led by Marco Baity-Jesi(SIAM department) in collaboration with Francesco Pomati(ECO department) and with the Swiss Data Science Center. The place of work will be at Eawag in Dübendorf and the PhD will be part of the D-USYS department at ETHZ.
Skills that we appreciate for this position
Strong motivation towards using machine learning applied to ecology
Fostering a healthy environment around you
Proactivity in interacting with colleagues within and outside of the team
Creativity and good communication skills
Comfort training machine learning models (e.g. with PyTorch)
Clean coding and scripting practices
Comfort with time series analysis
Basic knowledge on differential equations
Comfortable with mathematical manipulation and with translating math into code
Knowledge in community ecology especially plankton ecology
Since the project is interdisciplinary we do not expect you to excel in all these aspects before you start. We value self-awareness: If you believe you lack some of these skills but the project excites you you might be the right person for us. We do not evaluate based on so-called merit. We look for the person who is the best match for this position.
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 submitted by 5 November 2025 will be granted full consideration. These should include an application letter describing your interests and their relevance to this position a CV (without picture) and the names and contact information for two references.
For further information please contact 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.
Eawag: Swiss Federal Institute of Aquatic Science and Technology
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About Company
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 meetin ... View more
