Postdoctoral Research Fellow – Health Economic and Decision Sciences, Vaccines

Our company is on a quest for cures and is committed to be the world’s premier, most research-intensive biopharmaceutical company. Today, we’re doubling down on this goal. Our Research Division is a true scientific research facility of tomorrow and will take our company's leading discovery capabilities and world-class small molecule and biologics research and development expertise to create breakthrough science that radically changes the way we approach serious diseases.

Our Postdoctoral Research Fellow Program aims to be a best-in-industry program for industrial postdoctoral researchers. It is designed to provide the fellows unique research experiences with an academic focus in a commercial environment. With the resources, reach, and expertise of a large pharmaceutical company, postdoctoral researchers will be positioned to excel in an institution committed to breakthrough innovation in research and discovery development.

Position Overview:
This position resides within Vaccines, Health Economic and Decision Sciences (HEDS) department at Biostatistics and Research Decision Sciences (BARDS). HEDS provides strategic and analytic modelling expertise to measure and quantify the value of the company’s products. At BARDS, we value diversity and inclusion in our working environment where employees are enabled to develop and contribute.

As part of an agile team, the scientist will coordinate and collaborate on areas of interdependency, with modelling scientists, data scientists, IT partners and subject matter experts to ensure effective deployment of various types of models for vaccines, which will be used to simulate infectious disease spread, assess vaccine effectiveness at the population level, and evaluate key elements of vaccine trial designs.

Responsibilities include but are not limited to:
Reporting under a Senior Director and under the mentorship of a Principal Scientist, the postdoc fellow is expected to:
• Explore the integration of modelling methodologies, statistical methods, behavioural data, and epidemiological data into the estimation of contact structures/matrices and rates for compartmental models of infectious disease
• Develop methods to assess the quality of assumptions made for contacts in various models
• Develop excellent working relationships within partner across the research lab; ensure effective cross-functional collaboration across teams
• Collaborate externally and solicit input from appropriate stakeholders and scientific leaders
• Adopt latest estimation techniques from relevant published literature
• Disseminate key research findings/methodology via scientific congress presentations and publications in scientific journals

Education:
Candidates must currently hold a PhD or will receive a PhD by the end of 2023 in Mathematics, Statistics, or a closely related, quantitative field.

Required Experience and Skills:
• Previous experience with mathematical modelling of infectious disease
• Previous experience in mathematical analysis of contact assumptions in various model types, including metapopulation, stochastic, and network models
• Strong interpersonal, organizational and communication skills with ability to interact with individuals from a variety of disciplines

Preferred Experience and Skills:
• Working knowledge of a scientific programming language (Python, R, etc.)
• Previous experience in development of computational modelling tools designed for a wide range of audience
• Ability to communicate effectively in English in both verbal and written formats
• Great networking and professional communication skills