Postdoctoral position - Machine Learning Modeling of Arsenic Groundwater Contamination in Vietnam

The Inorganic Environmental Geochemistry group in the Department of Environmental Systems Science at ETH Zurich and Eawag, the Swiss Federal Institute of Aquatic Science and Technology, investigates processes that drive the biogeochemical cycling of trace elements across different environmental compartments, and how these cycles are affected by climate change and human activities. We are a group of interdisciplinary researchers combining field studies with biogeochemical analyses as well as statistical and mechanistic modeling. Our mission is to understand and predict environmental distributions of health-impacting trace elements to prevent health hazards, today and in future.

Consumption of groundwater contaminated with arsenic (As) poses a serious risk to human health, especially in South and Southeast Asia. This contamination is derived from geological sources from which As is biogeochemically released and transported in and across aquifers. One of the countries affected by As contamination is Vietnam, specifically the Red River and Mekong deltas on which the project is focused. The position advertised here is part of the larger SNSF-funded project “DeltAs - Evaluating delta-wide changes in geogenic arsenic contamination under anthropogenic pressures: An integrated approach to assess groundwater vulnerability in Vietnam”, which integrates hydrogeology, geochemistry, remote sensing and data science into a multidisciplinary framework to capture changes in As contamination patterns and their drivers in the Red River and Mekong deltas. Understanding such changes is crucial in determining strategies to mitigate As contamination and provide safe water resources for growing populations in these vulnerable regions.

In the frame of the DeltAs project, this postdoctoral position will investigate the spatially and temporally heterogeneous distribution of groundwater As contamination using modeling approaches. Furthermore, this position will investigate future scenarios of anthropogenic impact on the delta water systems and related groundwater As contamination. Areas of interest for this position include, but are not limited to, geostatistical modeling, interpretable and explainable machine learning, or hybrid modeling by combining process-based and data-driven approaches. Besides your own main project focus, you will contribute to the supervision of PhD and undergraduate students in the group.

• You have a PhD degree in environmental sciences, environmental engineering, data science, or related fields, or expect to obtain such a degree in early 2025.
• Excellent academic track record, with a strong background in machine learning methods and biogeochemistry.
• Programming experience using languages such as Python, R, etc.
• You are self-motivated, have critical thinking skills and the ability to work independently.
• You have an interdisciplinary and collaborative mindset, and desire to work with people from different disciplines and backgrounds.
• You are proficient in English, both verbally and written.

ETH Zurich is a family-friendly employer with excellent working conditions. We foster a modern and supportive group culture and value diversity, independence, and initiative. The position is embedded in an exciting and interdisciplinary research environment with connections to national and international project partners in Vietnam and the United States.

A competitive salary is paid according to the ETH standard. The initial contract duration is for one year, with possibility of extensions up to three years.