International Scientist - Spatial Data Science

1. Develop and deploy machine learning models using ground truth and remote sensing data to assess various aspects of ecosystem health at scale based on global datasets. This will include working with both optical and radar data and advanced machine learning frameworks including deep learning models.
   
2. Conduct spatial data (GIS) analysis tasks using R Python Julia and QGIS.
   
3. Contribute to the maintenance of the SPACIAL STAC.
   
4. Contribute to the development of monitoring systems and platforms.
   
5. Develop and deploy machine learning models using ground truth and remote sensing data. This will include working with both optical and radar data.
   
6. Engage with stakeholders and contribute to the development of trainings for CIFORICRAF staff and outside partners in spatial data analysis using languages such as R Python and Julia.
   
7. Represent CIFORICRAF at conferences and/or meetings from a technical remote sensing / data science perspective.
   
8. Manage spatial data science fellows and interns.
   

Requirements

• MSc or PhD in spatial data science remote sensing GIS or related field.
  
• Strong background in machine learning and AI.
  
• High level of proficiency in computer programming languages such as R Python or Julia.
  
• Experience in handling spatial data.
  
• Experience with Natural Language Processing (NLP).
  
• Experience with interactive decision support systems (eg. dashboards).