• As part of an agile team, the fellow will develop and support a seamless mechanism of coordination and collaboration in a dynamic area of interdisciplinary research

Collaboration with modeling scientists, data scientists, IT partners, subject matter experts and strategically leveraging generative AI to automate model extraction and facilitate rapid, intelligent adaptation across diverse settings, this project will profoundly enhance model transparency, dramatically accelerate deployment, and improve consistency in global health decision-making

• Reporting under a Senior Director within the Vaccines team within HEDS, the fellow is expected to:
• Build a robust corpus of health economic infectious disease models using AI-assisted systematic review techniques,
• Utilize advanced LLMs to precisely extract infectious disease model type, structure (states, transitions), and parameters (costs, utilities, probabilities),
• Implement an intelligent AI reasoning layer to evaluate consistency, completeness, and scientific validity across extracted models,
• Employ generative AI to propose new model structures, dynamically guided by disease-specific needs and prior evidence,
• Apply the developed pipeline to critical case studies (e.g., RSV vaccine modeling) and rigorously compare AI-generated models with existing approaches,
• Develop excellent working relationships within partner across our Research Laboratories; ensure effective cross-functional collaboration across teams,
• Collaborate externally and solicit input from appropriate stakeholders and adopt latest techniques from relevant published literature, and
• Disseminate key research findings/methodology via scientific presentations at congresses and publications in scientific journals

This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely

• Candidates should currently hold a PhD OR will receive a PhD by start of employment in Computer Science, Mathematics, Statistics, or a closely-related quantitative field
• Previous experience with large language models (LLMs), natural language processing (NLP), or machine learning,
• Previous experience working on interdisciplinary research projects and/or working within interdisciplinary teams,
• Ability to gather, organize, and synthesize complex information in order to draw conclusions and make recommendations,
• Strong creative problem solving skills,

Ability to communicate effectively in English in both verbal and written formats

• Strong programming skills in Python and/or C++, with experience in model fitting, simulation, and data extraction workflows,

Strong interpersonal, networking, presentation, and communication skills, and

• Under New York City, Colorado State, Washington State, and California State law, the Company is required to provide a reasonable estimate of the salary range for this job

Final determinations with respect to salary will take into account a number of factors, which may include, but not be limited to the primary work location and the chosen candidate’s relevant skills, experience, and education $75,000.00-$86,000.00 Available benefits include bonus eligibility, health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, and sick days