ILRI PhD Graduate Fellowship: Epidemiology, Agentic AI, and Integrated Wastewater Genomic Surveillance, Nairobi, Kenya Organization: International Livestock Research Institute (ILRI) Country: Kenya City: Nairobi Office: ILRI Nairobi The International Livestock Research Institute (ILRI) seeks to
recruit a PhD graduate fellow to work in the Epidemiology,
Agentic AI, and Integrated Wastewater Genomic
Surveillance project. The successful fellow will be hosted by
the Health program at ILRI. The International Livestock Research Institute (ILRI) works to
improve people's lives in low- and middle-income countries through
livestock science that contributes to equitable and resilient
Formation / Diplômes
livestock systems to deliver food systems transformation with
climate and environmental benefits. It is the only one of 15 CGIAR
research centers dedicated entirely to animal agriculture research
for the developing world. Co-hosted by Kenya and Ethiopia, it has
regional or country offices and projects in East, South and
Southeast Asia as well as Central, East, Southern and West Africa.
www.ilri.org The Health program's goal is to enhance the health and welfare
of farmed livestock, improve human well-being, and protect the
shared environment by strengthening control measures for animal and
agriculture-associated health risks. The program adopts a One
Health approach, recognizing the interconnectedness of human,
animal, and environmental health. By addressing disease risks at
this interface, the program aims to prevent the spread of zoonotic
and emerging infectious diseases that threaten public health and
food security. Read more here:
https: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 Lead the harmonization and integration of clinical infectious
disease and AMR datasets with wastewater metagenomic data. Map and align spatial and temporal dynamics between sewer
catchment populations and health facility data. Conduct epidemiological and statistical analyses to identify
associations between wastewater-derived pathogen/AMR signals and
clinical outcomes. Collaborate in the design and application of agentic AI tools
within GPAP to: Automate data ingestion, cleaning, and analysis workflows Detect anomalies, trends, and early warning signals Generate interpretable summaries for public health users Contribute to the development of interactive dashboards and
visualization tools for real-time surveillance, including: Pathogen and AMR trend monitoring Outbreak early warning indicators Spatial risk mapping Evaluate the predictive performance and operational utility of
GPAP tools in real-world public health scenarios. Engage with public health stakeholders to co-develop
user-centered outputs and ensure policy relevance. Contribute to implementation frameworks for integrating WBE and
AI-enabled analytics into national surveillance systems. Produce scientific publications, policy briefs, and technical
documentation. Minimum requirements for the ideal
candidate Master's degree in Epidemiology, Public Health, Global Health,
Biostatistics, or a related field. Proficiency in Python and/or R programming for data
manipulation and statistical analysis, including libraries such as
Expérience
pandas, scikit-learn, PyTorch or Tensorflow. Strong experience in epidemiological analysis and surveillance
systems. Proficiency with cloud platforms (AWS) and deployment of AI/ML
models. Experience with agentic frameworks Proficiency in version control and collaboration Git and
Github Familiarity with infectious disease epidemiology and AMR. Exposure to data visualization tools (e.g., R Shiny, Dash,
Tableau, Power BI) is desirable. Interest in or experience with AI/ML applications in public
Localisation
health is an advantage. Location: ILRI Kenya. Duration: 3 Years. Terms of appointment and stipend : ILRI will
offer a competitive stipend to cover living expenses in the project
location, medical cover, tuition costs and research expenses. The
successful candidate will be supervised jointly by ILRI scientists
and an academic supervisor. All applications MUST include the following (applications
without the below documents will not be considered): a cover letter expressing their interest in the fellowship
position and what they can bring to the fellowship. CV including names and addresses (including telephone and
email) of three referees who are knowledgeable about the
candidate's professional qualifications and work experience. academic qualification certificates/transcripts. Applications should be made to the Senior Manager, Capacity
Development, through our recruitment portal
http:number ILRI PhD GF/Health/02/2026 should be
clearly marked on the subject line of the cover letter. Tags development research disease surveillance global health interdisciplinary research public health Skills Epi Info Python R Programming Cloud Platforms Data Visualization Tools The recruiting organization, International Livestock Research Institute (ILRI), has not specified a closing date for this vacancy or continues to list jobs after their stated closing date.
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