Jobs:Job-00068
Apply before: 5 January 2020
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Posting:
Position: PhD opportunity
Apply before: 5 January 2020
Apply online:
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PhD position (m/f/x)
Subject: Towards improved model-based assessment of regional scale water quality status under current and future conditions
Project start / start of employment: 01.02.2020 .Working time 65% (25,35 hours per week), limited to 3 years
Your tasks:
Excessive nitrate surpluses – arising from large usages of agrochemicals (inorganic fertilizers) – are one of the main problems in agricultural areas, leading to subsurface pollutions (soil and groundwater) and eventually deterioration of the surface/subsurface water quality. Assessing the present level of subsurface contamination and providing future projections require an understanding of legacy components (the past trajectories), hydrologic and biogeochemical turnover processes through both data and mechanistic modeling approaches. To this end, we seek to provide improved system understanding of nitrate turnover process to ultimately improve model-based assessment of water quality status within the GlobeWQ project. Main tasks for this position include:
- Collection, processing and harmonization of input datasets for nitrate modelling (e.g., fertilizer, livestock, crop yield, in-stream N-concentration)
- Establishment/Enhancement of a nitrate model coupled to the existing multiscale Hydrologic modelling system (mHM).
- Understanding/synthesising the past (legacies) and future fate of Nitrate across the different terrestrial compartments (soil/groundwater/surface water).
- Active initiation of peer-review papers and preparation of publications as well as reports for the project.
- Representation of the project and its research at national and international meetings/conferences (e.g. EGU, AGU).
Your profile:
- Master degree in hydrological or water-related environmental sciences/engineering or Physics, Mathematics or Informatics
- Experience in hydrologic modelling activities with knowledge on subsurface biogeochemical (nitrate) processes
- Demonstrated programming skills (e.g., Fortran, Python, R)
- Ability to work in a multi-cultural environment
- Competences in communication, teamwork and scientific synthesis
- Excellent written and spoken English skill
