PhD Candidate: Climate Impacts on Water Quality

Master in Integrated Building Systems ETH Zürich

Zürich

Vor Ort

CHF 60.000 - 70.000

Vollzeit

Vor 6 Tagen
Sei unter den ersten Bewerbenden
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Zusammenfassung

ETH Zurich invites applications for a Doctoral Student position focused on the impacts of climate and hydrological extremes on water quality. Hosted by the Institute for Atmospheric and Climate Science at ETH Zurich and the WSL-SLF, within the NCCR CLIM+ program, the role combines data-driven modeling and climate research in a collaborative, international setting.

The selected candidate will study extreme events, develop predictive models, and disseminate findings through journals and

Qualifikationen

  • MSc degree in hydrology, climate sciences, environmental sciences, or a closely related field.
  • Strong hydrological process knowledge.
  • Experience in statistical and/or data-driven modeling.
  • Strong programming skills (Python and/or R).
  • Experience in working with large datasets, ideally hydrological, meteorological or climate observations/simulations.
  • Very good oral and written communication skills in English.
  • Command of one of the national languages is an asset.
  • Motivation to work in an interdisciplinary and international environment.

Aufgaben

  • Study the effect of climate and hydrological extremes on water quality.
  • Use data-driven insights to develop models predicting water quality under climate change.
  • Publish results in scientific journals and present at conferences.

Kenntnisse

Hydrology knowledge
Data-driven modeling
Python
R
Large datasets
English communication
Interdisciplinary collaboration

Ausbildung

MSc in hydrology/climate/environmental sciences

Tools

Python
R

Jobbeschreibung

ETH Zurich invites applications for a Doctoral Student position focused on the impacts of climate and hydrological extremes on water quality. Hosted by the Institute for Atmospheric and Climate Science at ETH Zurich and the WSL-SLF, within the NCCR CLIM+ program, the role combines data-driven modeling and climate research in a collaborative, international setting.

The selected candidate will study extreme events, develop predictive models, and disseminate findings through journals and

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