Digital and AI Solutions for Disaster Risk Reduction

Digital and AI Solutions for Disaster Risk Reduction

Attention! Please note that this is an Online Volunteering assignment. It's a short-term, task-based and non-contractual remote assignment; Online Volunteers are not UN Volunteers and do not receive any allowance or entitlements as part of the Online Volunteer assignment but receive a certificate of appreciation after successful completion. In addition, UNV is not involved in the selection process or collaboration.

Host entity: UNDP Switzerland

Advertisement end date: 2026-11-13T00:00:00

General

Description of assignment title: Digital and AI Solutions for Disaster Risk Reduction

Assignment country: Switzerland

Duration: 84 days

Sustainable Development Goal: 11. Sustainable cities and communities

Modality: Online

Work schedule: 16 - 20 hours per week

For how many hours per week will the volunteer be required?: 16 - 20 hours per week

Number of Assignments: 2

Details

Mission and objectives

UNDP is the UN's global development network, an organization advocating for change and connecting countries to knowledge, experience and resources to help people build a better life. We are on the ground in some 170 countries and territories, working with them on their own solutions to global and national development challenges as they develop local capacity, they draw on the people of UNDP and our wide range of partners.

Based in the middle of Europe, the UNDP Office in Geneva contributes to UNDP’s mission through serving as the UNDP Platform for Geneva and the Geneva-based organizations and as the primary point of contact with the governments of France and Switzerland.

Context

UNDP’s Disaster Risk Reduction and Recovery for Building Resilience Team (DRT) seeks support to integrate digital and artificial intelligence (AI) solutions into its knowledge products and services on disaster preparedness and early warning.

The DRT leads UNDP’s global practice on disaster risk reduction, recovery and resilience-building, providing policy advice and programmatic support to UNDP Regional Hubs and Country Offices in the design, implementation, monitoring and evaluation of disaster risk reduction and recovery programmes. This work is aligned with the UNDP Strategic Plan 2026-2029, where crisis resilience is one of four strategic objectives and digital and AI transformation a key accelerator, and with UNDP’s Action Agenda: Moving Beyond Crisis, which places development from day one at the centre of UNDP’s work before, during and after crises, from prevention and preparedness to response, recovery and transformation. Building on these frameworks, UNDP brings risk awareness to all its development work and strengthens the capacity of governments, institutions and communities to manage and prepare for multi-dimensional risks and shocks.

The UNDP Preparedness Toolkit is an interactive platform to better anticipate and prepare for uncertainty, risk and crisis. It enables UNDP to help countries strengthen their institutional, strategic and operational capabilities for preparedness and anticipation, improve the speed and efficiency of its programmatic solutions, and apply foresight to its development work, including in crisis settings. It also serves as a programmatic manual for Country Offices designing preparedness and anticipation projects in support of national and local priorities. Built on the Toolkit, the UNDP Preparedness Learning Pathway is a capacity development initiative that facilitates joint learning and knowledge exchange among decision-makers and practitioners from national and local authorities, UN entities and other in-country stakeholders, drawing on resources from UNDP and partners.

In line with the Strategic Plan’s focus on digital and AI transformation, the DRT is exploring how AI and data tools can make its products and services more interactive, accessible and useful for Country Offices, national and local authorities and partners. This includes embedding AI components into the Toolkit and the Pathway, developing interactive dashboards to track and visualize information, and identifying new AI applications to strengthen risk intelligence, early warning and preparedness.

UNDP is looking for two online volunteers with basic digital skills, curiosity about AI and an interest in disaster risk reduction, keen to apply digital tools to real-world development challenges. Selected volunteers will collaborate with the DRT, based in Geneva, gain hands-on experience in applying AI to disaster risk reduction, and learn about UNDP’s work on preparedness and early warning. They will also receive feedback on their collaboration and quality of work, a certificate of appreciation upon successful completion of the assignment, and credit of support where applicable.

Task type

Digital tool and software coaching

Task description

Under the guidance of the DRT Early Warning and Preparedness team, the online volunteers will support the following tasks:

AI components in existing products and services:

• Support the integration of AI components into the UNDP Preparedness Toolkit and the Preparedness Learning Pathway, such as AI-assisted search, virtual assistants or automated content summaries.
• Help prepare, structure and tag existing content so that it can be used effectively by AI tools.
• Test new AI features, document issues and suggest improvements to make them accurate, user-friendly and accessible.

Interactive dashboards:

• Support the design and development of interactive dashboards (e.g. Power BI or similar) to visualize learning, programme and risk-related information.
• Collect, clean and organize the data that feeds the dashboards.
• Support basic web design updates to present dashboards and digital products online.

Concept notes and research on AI for disaster risk reduction:

• Map existing AI applications in disaster risk reduction, early warning and preparedness, and identify good practices relevant to UNDP programming.
• Contribute to drafting short concept notes for AI solutions applied to disaster risk reduction, outlining the problem, intended users, data needs, potential risks and ethical considerations.
• Prepare short presentations to share findings with the team.

Proofs of concept:

• Develop proofs of concept to test the feasibility of AI solutions identified in concept notes, using open data and Python-based tools.
• Build and evaluate simple prototypes, such as predictive models, document analysis tools or geospatial analyses, and assess their performance against defined criteria.
• Document methods, results, limitations and lessons learned, and present findings to inform decisions on whether and how to scale.

Assignment requirements

Relevant experience: No experience required

Languages: English, Level: Fluent, Required

Required education level: Bachelor's degree Computer Science, Data Science, Statistics, Information Technology, Software Engineering, Geoinformatics/GIS, Environmental Science, Disaster Risk Management, or a related field.

Area(s) of expertise: Data science, information management, Artificial Intelligence, Emergency preparedness, crisis response

Driving license: -

Skills and experience

• Basic knowledge of disaster risk reduction, climate risk or early warning
• Hands-on experience with generative AI tools (e.g. ChatGPT, Copilot, Gemini, Claude) and interest in how AI can be applied to development challenges
• Coding experience in Python, including commonly used libraries for data analysis and visualization (e.g. pandas, NumPy, Matplotlib, seaborn, Plotly)
• Data science and machine learning skills, such as cleaning and analysing datasets, building predictive or classification models, and evaluating model performance (e.g. scikit-learn, XGBoost, PyTorch or TensorFlow)
• Familiarity with geospatial data or remote sensing (e.g. GeoPandas, rasterio, QGIS, Google Earth Engine) is an asset
• Basic IT and web skills, such as updating website content (e.g. WordPress, HTML) or building simple dashboards (e.g. Power BI, Looker Studio, Streamlit)
• Ability to explain technical concepts in simple, clear language
• Attention to detail and ability to work independently and meet deadlines in a remote setting
• Good communication and collaboration skills