Consultant - Multi-disease AI-Based Early Warning System
Remote US
IMACS /
Contract /
Remote
The Institute for Health Modeling and Climate Solutions (IMACS) is a global center of excellence at the intersection of climate change, health, and technology, under the Forecasting Healthy Futures (FHF) initiative launched by Malaria No More.
We are seeking a highly qualified and domain-experienced Consultant to support the development and deployment of the Multi-disease AI-Based Early Warning System for the ClimateSmart Indonesia initiative, funded by the Patrick J. McGovern Foundation and our multi-country project in collaboration with The Global Fund and The Task Force for Global Health. The Consultant will assist in finalizing country profiling reports, drafting technical documentation, tailoring AI codebases for country-specific requirements, developing training materials, and providing on-site training to Ministry of Health officials and public health managers, initially in Bangladesh, with potential deployments in other countries.
Key Responsibilities:
- Assist in detailed country profiling to gain insights into disease patterns, surveillance frameworks, and technological infrastructures of project countries.
- Draft comprehensive technical documentation, including data integration strategy, AI model architecture, and system workflows.
- Work in conjunction with the IMACS team to tailor the codebase for four countries in the Early Warning Surveillance project.
- Maintain GitHub repositories to enable efficient version control and collaborative development.
- Refine local epidemiological and climate data-driven AI-based predictive modeling techniques.
- Ensure algorithm customization aligns with country-specific public health data regulations.
- Assist in validation and optimization of outputs from the AI system by working closely with technical teams.
- Participate in the design of front-end interfaces to enhance interactive disease monitoring dashboards.
- Develop cloud-native applications to implement scalable and efficient disease EWS systems.
- Prepare training materials (presentations, manuals, SOPs) focusing on Ministry of Health officials and public health managers.
- Conduct in-person and virtual training sessions to ensure effective system adoption and utilization.
- Provide technical guidance and troubleshooting support post-training to address implementation challenges.
- Engage with project stakeholders for the smooth deployment of EWARS systems.
- Develop policy briefs and strategic recommendations to enhance AI-driven EWS frameworks.
1. Country profiling & technical documentation:
2. Customization & implementation:
3. Training & capacity building:
4. Stakeholder Engagement & Knowledge Transfer:
Required Qualifications & Experience:
- Master's or PhD in Public Health, Epidemiology, Data Science, Computer Science, or related fields.
- Proficiency in Python, React, and other programming languages is essential.
- 5+ years of experience in digital health projects, disease surveillance, or health informatics.
- Hands-on experience with AI/ML model implementation and customization in a healthcare setting.
- Experience in training and capacity building for government or healthcare professionals.
- Prior experience with BI frontend development is a plus.
- Expertise in deploying and managing cloud-native applications for large-scale AI-driven solutions is preferred.
- Familiarity with GitHub for version control and collaborative software development.
Key Competencies:
- Excellent technical writing and documentation skills.
- Ability to communicate complex AI concepts to non-technical stakeholders.
- Proven ability to work in a multicultural, cross-functional team.
- Strong project management skills with attention to detail.
- Willingness and ability to travel for on-site training and stakeholder engagement.
$2,500 - $5,000 a month
Malaria No More is an equal opportunity employer. We encourage applicants of all backgrounds to apply and do not discriminate based on race, color, religion, gender, national origin, age, disability, or any other protected characteristic.
