Senior AI Fellow, Center for Vaccine Innovation and Access (CVIA)

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PATH is a global nonprofit dedicated to achieving health equity. With more than 40 years of experience forging multisector partnerships and with expertise in science, economics, technology, advocacy, and dozens of other specialties, PATH develops and scales up innovative solutions to the world’s most pressing health challenges.
About the role
PATH’s AI Initiative is pioneering the use of generative AI and other advanced digital technologies to accelerate biomedical discovery, strengthen regulatory systems, and enhance the safety and scalability of digital healthcare. Working under the supervision of the Deputy Director (AI4Science), the Senior AI Fellow will be a key member of the AI Initiative. This role has been created specifically to bring AI methods directly into PATH’s Center for Vaccine Innovation and Access (CVIA) science and operations, a world-leading division of PATH that has helped develop and introduce more than two dozen vaccines over the past three decades.
PATH’s Center for Vaccine Innovation and Access (CVIA) brings together our expertise across every stage of the long and complex process of vaccine research, development, and delivery to make lifesaving vaccines widely available to children and communities across the world. CVIA’s current portfolio encompasses more than two dozen vaccines either in development or already in use to protect against fifteen different diseases. Our focus is on vaccines to address the leading diseases that claim children’s lives worldwide: pneumonia, diarrheal disease, and malaria; as well as other global health priorities, such as polio and meningitis. We work in partnership with national health ministries, pharmaceutical manufacturers, donors, international financing and regulatory organizations, and many others. PATH has led numerous global partnerships, including the award-winning Meningitis Vaccine Project and the Malaria Vaccine Initiative, which helped develop the first malaria vaccine candidate recommended for pilot implementation.
The Senior AI Fellow will spend most of their time embedded in CVIA’s work, while remaining a full member of the AI Initiative team, with access to an established technical and thought-leading community, shared methods and infrastructure, and direct support for their growth as a global health AI practitioner and scientist.
Candidate Profile
The Senior AI Fellow will have a strong computational or quantitative background with demonstrated experience in vaccine development. While they might not have formally trained as an immunologist or vaccinologist, they will have spent enough time working in this space to understand how vaccines move from discovery through to market.
The core of their day-to-day work will be applying AI and computational methods to CVIA’s research and operational questions within agreed priorities and technical direction. This could include drawing on CVIA’s trial design and level-of-effort data to support estimation and planning tools, applying AI methods to chemistry, manufacturing, and controls challenges such as formulation or process optimization, or supporting operational decisions where CVIA’s institutional experience is the key asset and AI helps make it more usable.
It could also include agentic AI workflows to support the identification of novel correlates of protection, AI Co-Scientist tools applied to antigen design and selection, or support for analyzing immunogenicity and trial data. These are deep research problems tackled with scientific rigor and methodological ambition, using data ranging from operational to biological.
This is a hands-on role for someone who wants to work at the intersection of AI and vaccine science and operations. The role may suit a vaccine scientist with hands-on fluency in modern AI systems or a computer scientist with experience in biomedical research. If you want to apply frontier AI to real global health challenges, as part of a team that has taken vaccines from the lab to the people who need them, this could be the role for you.
Please apply by Sunday, November 1, 2026 end of day for priority consideration.
Core Responsibilities
Solution Design and Scoping
Serve as a trusted, day-to-day technical resource for the Deputy Director and CVIA colleagues on what AI and computational tools can and cannot usefully do.
Work with colleagues, from senior leadership to bench scientists, to assess and recommend which problems are well suited to AI-assisted approaches, using agreed criteria and with guidance on priorities and final direction.
For agreed use cases, develop and propose the technical approach, success measures, identification of available or required data and domain expertise, and development of a realistic project plan.
Product Development
Apply rigorous quantitative research methods, including machine learning and statistical analysis, alongside AI methods such as prompt engineering and agent architecture design, to develop robust solutions for operational and scientific use cases within the CVIA portfolio.
Build and iterate on AI-enabled tools and workflows that address defined CVIA needs, from predictive models for trial planning using CVIA’s historical data, to machine learning applied to CMC challenges such as formulation optimization, to LLM-based pipelines for evidence synthesis.
Independently deliver assigned technical workstreams within agreed objectives, scope, methodology, and review points, from data exploration through production of a working tool or analysis.
Use Python-based development, LLM APIs, agentic frameworks, and close collaboration with CVIA subject-matter experts who provide domain knowledge and validation.
Applied Analysis and Research
Contribute to ongoing AI-related work across the CVIA portfolio, spanning operational improvement and scientific discovery. Current examples include using LLMs for evidence synthesis, leveraging AI Co-Scientist tools to support work on correlates of protection and trial data analysis, and using human-centered design principles to develop a wireframe for an agentic workflow that can generate regulatory strategies.
Pair computational skills with the domain expertise of CVIA scientists and lead or contribute to publishable outputs where the results warrant it.
Proactively identify and propose new use cases as CVIA’s priorities evolve, for consideration and prioritization by the Deputy Director and relevant CVIA leadership.
Secondary Responsibilities
Business Development
Support business development activities at the intersection of AI and vaccine innovation and access, under the supervision of the relevant CVIA and AI team leadership.
Provide technical input to CVIA staff considering opportunities that could leverage AI, including drafting technical contributions for proposals, reviewing AI-relevant proposal components, and supporting the identification of partners or solutions.
Project Support and Coordination
Support the Deputy Director and CVIA leadership in ensuring timely delivery of assigned AI project outputs, including compliance with PATH and donor research ethics and data protection standards.
Coordinate between CVIA and the AI Initiative, bringing emerging tools and methods to CVIA and keeping the wider Initiative informed about CVIA’s operational realities.
Learning and Professional Development
Stay current with developments in vaccine science and AI for science, and contribute to the scoping, development, and delivery of training that helps upskill CVIA staff in AI methods and solutions relevant to their work.
Contribute to CVIA’s and PATH’s thought leadership on AI in vaccine development through peer-reviewed scientific articles, conference presentations, blog posts, and external engagement.
Minimum Qualifications
PhD, or equivalent research experience, in computational biology, biostatistics, or a closely related quantitative discipline, with a focus on vaccine development, infectious disease, or the operational and manufacturing challenges associated with either. Alternatively, a PhD in vaccinology, immunology, or a related biomedical field with strong and demonstrable computational skills developed through research or applied practice.
Documented and measurable impact applying computational or AI/ML methods in a vaccine development, infectious disease, or closely adjacent research setting, whether through academic research, industry, or applied public health work.
Practical experience applying AI or machine learning methods to a scientific or operational problem, such as using large language models for literature synthesis or hypothesis generation, building or fine-tuning predictive models, or working with agentic workflows and prompt engineering. This could come from a research project, an industry role, or substantial self-directed work, as long as it is concrete and demonstrable.