The chosen candidate will have a master's degree in geosciences, environmental sciences, remote sensing, civil engineering, applied mathematics, computer science or a related domain.
A requirement for this position is a good base in applied mathematics and programming. Knowledge in geostatistics or machine learning applied to spatial data, experience in handling remote sensing or climate datasets are advantages.
Candidates will be committed to conducting a PhD thesis on numerical and statistical modeling involving Earth surface imagery. They will have an interest in spatial models, large datasets and algorithmic development.
Excellent skills in written and oral English are required. Working knowledge of French language is preferable but not necessary.
A minimum of 50% of the workload will be devoted to a PhD thesis in Earth surface modeling. This work will include the use of existing data (satellite imagery, climate models outputs, historical climate data) to develop numerical representations of the Earth surface and its evolution.
A maximum of 50% of the workload will consist in assisting with teaching and research duties: teaching activities under the supervision of a professor, research work not related to the personal PhD topic, technical and administrative tasks related to the activities of the Institute.
The employment conditions are available here.