ILRI PhD Graduate Fellowship: Epidemiology, Agentic AI, and Integrated Wastewater Genomic Surveillance

International Livestock Research Institute (ILRI)

The International Livestock Research Institute (ILRI) works to improve food security and reduce poverty in developing countries through research for better and more sustainable use of livestock. ILRI is a CGIAR research centre - part of a global research partnership for a food-secure future.

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https://www.ilri.org/

ILRI PhD Graduate Fellowship: Epidemiology, Agentic AI, and Integrated Wastewater Genomic Surveillance

The position

ILRI and the Genomic Pathogen Analysis Platform (GPAP) at the Technical University of Denmark (DTU) are advancing next-generation approaches for pathogen surveillance by integrating genomics, epidemiology, and artificial intelligence. A key focus is the development of agentic AI tools capable of automating complex analytical workflows, from metagenomic data processing to actionable public health insights.

Building on a large-scale wastewater-based epidemiology (WBE) initiative with longitudinal metagenomic sequencing data from 30 urban sites, this PhD project will integrate environmental genomic data with clinical surveillance data. The project will leverage GPAP’s infrastructure to develop AI-driven, semi-autonomous (“agentic”) analytical pipelines and interactive dashboards that translate complex data streams into real-time decision-support tools for public health systems.

Terms of reference

  1. Lead the harmonization and integration of clinical infectious disease and AMR datasets with wastewater metagenomic data.
  2. Map and align spatial and temporal dynamics between sewer catchment populations and health facility data.
  3. Conduct epidemiological and statistical analyses to identify associations between wastewater-derived pathogen/AMR signals and clinical outcomes.
  4. Collaborate in the design and application of agentic AI tools within GPAP to:
    1. Automate data ingestion, cleaning, and analysis workflows
    2. Detect anomalies, trends, and early warning signals
    3. Generate interpretable summaries for public health users
  5. Contribute to the development of interactive dashboards and visualization tools for real-time surveillance, including:
    1. Pathogen and AMR trend monitoring
    2. Outbreak early warning indicators
    3. Spatial risk mapping
  6. Evaluate the predictive performance and operational utility of GPAP tools in real-world public health scenarios.
  7. Engage with public health stakeholders to co-develop user-centered outputs and ensure policy relevance.
  8. Contribute to implementation frameworks for integrating WBE and AI-enabled analytics into national surveillance systems.
    1. Produce scientific publications, policy briefs, and technical documentation.

Minimum requirements for the ideal candidate

  1. Master’s degree in Epidemiology, Public Health, Global Health, Biostatistics, or a related field.
  2. Proficiency in Python and/or R programming for data manipulation and statistical analysis, including libraries such as pandas, scikit-learn, PyTorch or Tensorflow.
  3. Strong experience in epidemiological analysis and surveillance systems.
  4. Proficiency with cloud platforms (AWS) and deployment of AI/ML models.
  5. Experience with agentic frameworks
  6. Proficiency in version control and collaboration Git and Github
  7. Familiarity with infectious disease epidemiology and AMR.
  8. Exposure to data visualization tools (e.g., R Shiny, Dash, Tableau, Power BI) is desirable.
  9. Interest in or experience with AI/ML applications in public health is an advantage.

Method of application

If you are interested and qualified, kindly submit your application via the link provided below,

https://www.ilri.org/join-us/jobs-careers?jid=61057-ilri-phd-graduate-fellowship-epidemiology-agentic-ai-and-integrated-wastewater-genomic-surveillance&utm_source=Jobinkenya

Deadline 03/06/2026

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