Senior Machine Learning Specialist

ADPC is an autonomous international organization established for scientific, educational, developmental, and humanitarian purposes with a vision of safer communities and sustainable development through disaster risk reduction and climate resilience in Asia and the Pacific. Established in 1986 as a technical capacity building center, ADPC has grown and expanded its role to be for scientific, educational, developmental and humanitarian purposes. ADPC employs a wide range of professional expertise typically required for Disaster Risk Reduction (DRR) and Climate Resilience (CR) in an effective manner.

ADPC develops and implements cross‑sectoral projects/programs on the strategic themes of risk governance, urban resilience, climate resilience, health risk management, preparedness for response and resilient recovery. Our strategic themes are complemented and underpinned by the cross‑cutting themes of gender and diversity, regional and transboundary cooperation as well as poverty and livelihoods.

Through its work, ADPC supports the implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030, the Sustainable Development Goals (SDGs), the New Urban Agenda, the United Nations Framework Convention on Climate Change, the agenda defined at the World Humanitarian Summit in 2016, and other relevant international frameworks.

The Risk Analytics and Climate Services Department is a multi-disciplinary team of experts committed to providing innovative, science‑based solutions for actions to adapt to climate change and mitigate the impacts of disasters. The innovations include uses of geospatial technology, satellite data, numerical models, cloud computing, and artificial intelligence for assessing vulnerability and risk, generating climate data, developing early warning systems, forecasting possible climate impact, and informing anticipatory actions.

These lead to risk‑informed developments in the sectors such as agriculture, transportation, water resources, energy, communications and health.

The department also applies advanced geoinformatics and climate analytics to address water and food security issues by assessing water availability and water-use efficiency, groundwater monitoring, assessing drought risks, and optimizing agricultural productivity, hence ensuring sustainable water and food systems in vulnerable regions. The department promotes Nature‑Based Solutions by leveraging ecosystem services such as wetland restoration, agroforestry, and green‑gray infrastructure to reduce disaster risks and build climate resilience.

Lastly, the department produces risk analytics and integrates them into urban plans and engineering designs of critical infrastructures, hence improving their resilience to disasters and climate change. With a commitment to science‑based approach, the department envisions empowering stakeholders to reduce risks, adapt to climate change, and build more resilient communities and ecosystems.

Under the project SERVIR Southeast Asia (SERVIR SEA), ADPC utilizes advanced technology including satellite Earth Observation data, geospatial models and analytics, and Artificial Intelligence (AI) for developing practical and accessible solutions for Southeast Asia. The applications of the advanced technologies required extensive validations of the assumptions and results produced, assessments of the accuracy of the outputs, and transfers of the knowledge to the people in Southeast Asia, including ADPC staff.

To address these specific demands, ADPC seeks part‑time Senior Machine Learning Specialist to work closely with the ADPC team on the above‑mentioned tasks.

The consultant is expected to deliver the following outputs:

• A Machine Learning based workflow and data pipeline on the following work component:
  • Environmental Drivers of Disease Dynamics in Thailand
  • Monitoring Mining Expansion and Environmental Impacts on River Systems in Myanmar
• Training for ADPC on machine learning models and their applications
• Peer‑reviewed publications

The consultant will undertake the following tasks:

• Lead the design and implementation of Machine Learning approaches and technical models
• Con…