MIning MUlti-source and MUlti-modal geo-referenced information (MIMU)
Applicants are invited for the position of Post-Doctoral Research Fellow as part of a joint research project between INESC-ID and NOVA.LINCS, related to the general field of Geospatial Artificial Intelligence.
The project, titled MIning MUlti-source and MUlti-modal geo-referenced information (MIMU), focuses on the study of machine learning approaches for the discovery and mapping of innovative geographic knowledge through the analysis and processing of large-scale volunteered data (e.g., geo-referenced multimedia contents such as images and textual descriptions, posted on social-media platforms like Flickr, Twitter, or Foursquare), in combination with more traditional sources (e.g., remote- sensing products available in the context of initiatives like ESA’s Sentinel/Copernicus programme, and/or tables with socio-demographic data made available by statistical offices). Ongoing activities within the context of the project include the usage of deep learning methods for:
– Segmentation of high-resolution aerial imagery, e.g. in the context of mapping flooding extents in urban regions.
– Proximate sensing and mapping with ground-level imagery;
– Remote sensing image captioning;
– Geographical text analysis.
A PhD in Computer Science, Computer Engineering, Geomatics, Electrical Engineering, Geographical Information Sciences, or other related fields. Preference will be given to candidates with previous experience in data science and machine learning, and with an established track record evidenced by publication in top quality journals and conferences.
Detaied information about the position package and application requirements:
Feel free to contact us with any questions: