ETH Zürich

PhD position on machine learning based predictions of river flow and water temperature in a changing climate

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PhD position on machine learning based predictions of river flow and water temperature in a changing climate

The Land-Climate Dynamics group at ETH Zürich is looking for a Doctoral candidate to leverage machine learning to investigate changes in Swiss water temperatures and river flow in support of energy system science.The Land-Climate Dynamics group at ETH Zürich is looking for a Doctoral candidate to leverage machine learning to investigate changes in Swiss water temperatures and river flow in support of energy system science.

Project background

Both river flow volumes and water temperature are essential factors in the energy system as they directly influence generation of hydropower and impact the cooling efficiency of thermal power plants. In Switzerland, anthropogenic climate change is affecting both water quantity and temperatures in rivers and streams thereby raising legitimate questions on associated risks to the energy system. To advance our understanding of climate change impacts on water flow volumes and temperature, the goal is to build on recent advances in using machine learning for hydrological modelling to develop spatially contiguous data-driven models of daily water temperature and river flow in Switzerland. These will be linked with climate projections to investigate to what extent climate change is increasing the risk of riverine heatwaves - relevant to thermal power plants - and hydrological droughts – which may be a threat to hydropower production.

The research will be conducted within the RECIPE (Resilient Infrastructure for the Swiss Energy Transition) project that is funded by the SWiss Energy research for the Energy Transition (SWEET) program in collaboration with the National Centre for Climate Services (NCCS).

Job description

As a doctoral student you will conduct quantitative and theoretical research at the interface between hydrological and climate sciences and investigate approaches that allow for a joint prediction of flow volumes and water temperatures at ungauged locations in Switzerland. This involves applying deep learning methods to in-situ observations and to use the resulting models in together with climate model simulations to explore past and future extremes of flow volumes and water temperatures across Switzerland.

Profile

  • You hold a master’s degree in climate/environmental science, hydrology, physics, statistics, applied math, computer science or a related field (or you will graduate soon).
  • You are a creative personality and enjoy solving scientific problems independently as well as in team efforts.
  • You have a strong interest in terrestrial climate variability and hydrological extremes.
  • You are passionate about using quantitative methods with focus on statistical data analysis and/or large-scale physical modelling.
  • You have a good command of scripting languages suitable for data analysis (e.g. Python), knowledge of machine learning libraries (e.g. PyTorch) is beneficial.
  • You have good command of spoken and written English.

We offer

Working, teaching and research at ETH Zurich

We value diversity

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Curious? So are we.

We look forward to receiving your online application with the following documents:

  • Application letter in which you outline your motivation and research interest (max. 1 page).
  • Curriculum Vitae including an overview of relevant courses taken and a list of publications (if any)
  • Names and contact details of two professional referees.

Screening of applications will start end of October.

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about the institute for Atmospheric and Climate Science can be found on our website. Questions regarding the position should be directed to Lukas Gudmundsson, lukas.gudmundsson@env.ethz.ch (no applications). Administrative requests should be directed to Rahel Buri, rahel.buri@env.ethz.ch.

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Lisätietoa työpaikasta

Otsikko
PhD position on machine learning based predictions of river flow and water temperature in a changing climate
Työnantaja
Sijainti
Rämistrasse 101 Zürich, Sveitsi
Julkaistu
2024-10-01
Viimeinen hakupäivä
Unspecified
Työpaikan tyyppi
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Tietoja työnantajasta

ETH Zürich is well known for its excellent education, ground-breaking fundamental research and for implementing its results directly into practice.

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