Jobs:Job-01252

From CSDMS
Postdoc position: Machine Learning for Flood and Drought Modeling under Climate Change
Charles University, Prague, , Czech Republic
Apply before: 21 July 2023


We invite excellent young researchers to apply for a postdoctoral position focused on machine learning for flood and drought modeling under climate change.


This is a full-time position for a period of 12 months, starting from January 1, 2024, with a salary of 1000 EUR/month. The position is opened in the Research Group of Hydrology (http://hydro.natur.cuni.cz/), Department of Physical Geography and Geoecology, at Faculty of Science (https://www.natur.cuni.cz/eng?set_language=en), Charles University in Prague, Czech Republic (https://cuni.cz/UKEN-1.html). The position will be funded by the JUNIOR Fund of Charles University (https://cuni.cz/UKEN-178.html).

The research project aims at advancing the application of machine learning methods to analyze the simultaneous effects of climate change and landscape disturbance on extreme hydrological processes and the uncertainty in their predictions. The research should lead to more reliable simulations of dynamic natural systems under changing boundary conditions, reduce uncertainties in predictions, and disentangle cross effects of the main drivers of hydrological change.

This project will be carried out under the supervision of prof. Jakub Langhammer (https://langhammer.natur.cuni.cz/). The candidate will be involved in the ongoing research projects of the research group focusing on the hydrological impacts of climate change on peat and snow hydrology. We expect the candidate to publish results in high quality hydrological journals such as Journal of Hydrology, Hydrology and Earth System Sciences, or Water Research.

To apply, please submit the required documents to jakub.langhammer@natur.cuni.cz (project supervisor) and copy pavla.pouskova@natur.cuni.cz (International Department). More information can be found at https://stars-natur.cz/postdoc-positions/geography/machine-learning-for-flood-and-drought-modeling-under-climate-change?back=v7zpo.

Of interest for:
  • Terrestrial Working Group
  • Hydrology Focus Research Group
  • Artificial Intelligence & Machine Learning Initiative