This PhD project, hosted by the Geoscience and Engineering Department of the TUDelft, is a unique opportunity to shape our understanding of geological evolution and the impact it will have on future landscapes and water resources in northern Africa (in this project: above the equator). Positioned at the intersection of tectonic geomorphology and hydrogeology, this project is not just about forecasting; it’s about forming practical findings for mitigating the challenges of demographic growth and climate change. Through a multidisciplinary approach that makes use of landscape evolution modelling (BADLANDS), you will lay the groundwork for pivotal policy-making and sustainable resource management strategies that may have impact in the centuries to come. This project links to the UN Sustainable Development Goal #6 ‘clean water and sanitation’ as well as forecasting impacts on one of the Planetary Boundaries, namely ‘land-system change’.

The research undertaken will address critical questions concerning the future landscapes of northern Africa and the sustainability of water resources, vital for both environmental conservation and the well-being of local populations. The work will not only inform our understanding of geological landscape evolution but also provide insights into the influence on forecasted demographic growth and climate change, offering potential solutions to mitigate future challenges (~4D stress maps/climate resilience mapping)

If you are passionate about geoscience, hydrogeology, predictive modelling, and about applying your knowledge to give answer to societal problems, this role offers the chance to make a significant impact on our shared future.

Qualifications

An M.Sc. in a relevant field, such as Geology, Hydrogeology, Geomorphology, Environmental Geology, Physical Geography, or Geo-modelling. We also encourage you to apply if you come from another quantitative background as geological training may be provided.

1. Proficiency in programming
2.  Basic GIS skillset
3. Previous experience in Landscape Evolution Modelling
4. Affinity with the studied region