At Skylab Analytics we believe that the big problems of the century are to be solved with the help of satellite imagery, machine learning and artificial intelligence. Our mission is to apply our technology to help solve problems related to food security, climate change, limited resources and sustainable development.
Wildfires destroy millions of square kilometers of forest worldwide every year. In some countries such as the US, the total burned area (and fire size) has consistently increased over the last decades. Portugal has seen a similar trend in burned area over the last couple of decades, where an area larger than the size of Belgium has burned since. Last year Portugal had the largest total burned area in a year over the past decade and it has recently experienced the worst record in half-century in terms of casualties.
Skylab Analytics is seeking to develop (near) real-time fire risk monitoring and detection technology within a non-profit project. We aim to apply the data-driven artificial intelligence and machine learning (AI&ML) approach that tech companies such as Amazon, Facebook or Google use in their daily business.
To help us with this project we seek a talented, independent, and resourceful summer intern or tech volunteer specialised in either Geography, Environmental or Forestry Engineering. The aim of this R&D Summer Internship / Tech volunteering work is to link both scientific and operational domain expertise in wildfire risk forecasting and management, applying a tech-based geospatial big data artificial intelligence approach. We are looking for someone preferably based in Portugal, open to work remotely.
You will research the state-of-the-art wildfire risk forecasting, identifying existing key research and data-sources, and manage the data gathering from the several stakeholders. You will collaborate with Skylab Analytics and partners to define the technical and operational requirements for (near) real-time wildfire risk forecasting and monitoring using geospatial and satellite data.
The region of focus for this project is the centre of Portugal, where you will work closely with the local stakeholders, gather both operational requirements and manage datasets to be ingested into AI&ML learning algorithms.
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