Research on AI & Digital Public Infrastructure for Climate-Smart Agriculture
Contribute to research and knowledge support for climate-smart agriculture initiatives.
This opening expired 26 days ago.
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Overview
Contribute to research and knowledge support for climate-smart agriculture initiatives.
You have:
- Master’s degree or equivalent in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, Agricultural Informatics, or a related field. PhD candidates are encouraged to apply.
- Strong research and analytical skills.
- Ability to synthesize technical information and present findings clearly.
- Knowledge of Data Science, Machine Learning, Deep Learning, and Natural Language Processing.
- Familiarity with geospatial technologies, digital public infrastructure, or agricultural data systems is desirable.
- Prior research experience in academic or interdisciplinary projects will be an advantage.
- Ability to work independently and meet agreed timelines.
Contract
This is a UNV contract. More about UNV contracts.
The assignment is anchored in the BMGF-supported project “Localizing Data Science for Climate Change Adaptation”, which is being implemented across Bihar, Odisha, Madhya Pradesh, and Uttarakhand. The project aims to strengthen climate-resilient agriculture by integrating local knowledge with data science, geospatial technologies, digital public infrastructure, and climate advisory systems.
The Online Volunteer will contribute to research and knowledge support for these initiatives, with a focus on climate-smart agriculture, digital agriculture, and AI applications for smallholder farming systems.
Under the supervision of the Project Lead, BMGF Project, Action for Climate and Environment, UNDP India, the Online Volunteer will support research and knowledge management related to AI and digital public infrastructure for climate-smart agriculture. Key tasks include: • Conduct background research, literature reviews, and analysis on AI applications in climate-smart agriculture. • Support preparation of a report, policy brief, presentations, and knowledge products. • Assist in documenting the project progress, maintaining internal knowledge repositories, and organizing reference materials. • Support analysis of geospatial and digital agriculture initiatives • Contribute to communication materials, case studies, and technical documentation being developed by the Action for Climate and Environment on climate-smart agriculture
Master’s degree or equivalent in Computer Science, Computer Engineering, Artificial Intelligence, Data Science, Agricultural Informatics, or a related field. PhD candidates are encouraged to apply.
Required Skills and Experience • Strong research and analytical skills. • Ability to synthesize technical information and present findings clearly. • Knowledge of Data Science, Machine Learning, Deep Learning, and Natural Language Processing. • Familiarity with geospatial technologies, digital public infrastructure, or agricultural data systems is desirable. • Prior research experience in academic or interdisciplinary projects will be an advantage. • Ability to work independently and meet agreed timelines.
Potential interview questions
| Can you provide an example of a research project that required you to analyze technical information and present your findings? | This question assesses your analytical and communication skills in research contexts. | Discuss a specific project where you successfully analyzed data or information and clarify how you communicated those findings. |
| Describe a time when you had to integrate knowledge from different fields to solve a problem. What was your approach? | This question evaluates your interdisciplinary research capabilities. | Pro members can see the explanation. |
| What digital tools or technologies have you used in previous research projects? How did they support your work? | Pro members can see the explanation. | Pro members can see the explanation. |
| Can you explain your understanding of climate-smart agriculture and its importance? | Pro members can see the explanation. | Pro members can see the explanation. |
| Tell us about a time you faced a challenging timeline. How did you manage your tasks? | Pro members can see the explanation. | Pro members can see the explanation. |
| Describe a situation where you had to document project progress. How did you ensure accuracy? | Pro members can see the explanation. | Pro members can see the explanation. |
| Have you worked with machine learning or AI applications before? Can you provide an example? | Pro members can see the explanation. | Pro members can see the explanation. |
| What motivated you to apply for this volunteer opportunity? | Pro members can see the explanation. | Pro members can see the explanation. |
Added 1 month ago
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Updated 26 days ago
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Source:
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