Artificial Technology Intern

Requirements

• Be enrolled in, or have completed, a graduate school programme (second university degree or equivalent, or higher) in artificial intelligence, data science, computer science, or environmental science;
  
• Be enrolled in, or have completed, the final academic year of a first university degree programme (minimum bachelor’s degree or equivalent) in artificial intelligence, data science, computer science, environmental science, or a related field with demonstrated experience or coursework in AI and automation tools applications.
  
• Applicants to the UN Internship Programme are not required to have professional work experience.
  
• However, a field of study that is closely related to the type of internship that you are applying for is required.
  
• Applicants must be a student in the final year of the first university degree (bachelor or equivalent), Master’s or Ph.D. Programme or equivalent, or have completed a Bachelor’s, Master’s or PH.D. Programme.
  

• supporting the drafting of CBIT Project Identification Forms (PIFs) and GEF-9 concept notes by developing or applying AI- or automation-based tools to identify country needs, gaps, and opportunities ;
  
• using technologies such as Power Platform, natural language processing (NLP) and machine learning (ML) to extract insights, automate tasks, or improve data management;
  
• developing data visualizations and dashboards to support project design and monitoring;
  
• researching and documenting emerging applications of AI and automation in climate transparency, mitigation, and project development;
  
• contributing to the preparation of technical briefs, presentations, and knowledge products;
  
• participating in brainstorming sessions to explore innovative uses of AI and automation in national GHG inventory systems, MRV frameworks, and climate data platforms;
  
• supporting the organization of virtual consultations, webinars, and workshops with stakeholders and experts; and assisting with documentation and follow-up of project development milestones.