Open position – 15 month contract – founded by the MAESTRIA project full information here
The work is dedicated to the fusion of heterogeneous information coming from different satellite sensors in order to improve the accuracy and semantic richness of the produced land cover maps. In MAESTRIA, a new pivotal representation of the multi-modal data will be developed in order to minimize the loss of information with respect to the original data: a set of common variables to all modalities sampled at 10m resolution and daily revisit. Two main approaches will be developed in parallel: one based on (1) physical approaches (models of the landscapes and the measuring mechanisms) and the other one based on purely (2) statistical approaches. We will pay special attention to the possibility of cross-pollination of the two approaches. The specific tasks of the job cover the implementation and the evaluation of representation learning algorithms (deep learning networks). The work will be done under the supervision of the MAESTRIA researchers.
• Master’s or PhD in Applied Mathematics, Computer Science or Machine Learning
• Good programming skills in Python, knowledge of Pytorch will be highly appreciated
Candidates should send an e-mail to firstname.lastname@example.org including: 1. Full CV 2. Letter of interest 3. Contact information for two references