Associate Scientist, Post Doctoral Fellow- Epstein-Barr Virus & Multiple Sclerosis - Hybrid

Job Description Be a part of the legacy: Postdoctoral Research Fellow Program Position Overview Our Research Laboratories' Postdoctoral Research Fellow Program aims to be a best-in-industry program for industrial postdoctoral researchers, designed to provide you 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. As a Postdoctoral Research Fellow in the Department of Epidemiology, you will contribute to the important study of viral immune and autoimmune responses following Epstein Barr Virus (EBV) infection, and how these immune responses may lead to multiple sclerosis (MS), a neurodegenerative disease that causes significant morbidity. You will collaborate closely with a multidisciplinary team of scientists from the EBV and neurology disease areas, including clinical development and epidemiology. In this role, you will use advanced analytic methods, including machine learning and omics approaches, to identify patterns in host immune response associated with multiple sclerosis (MS). These findings can generate new hypotheses and identify biomarkers that predict multiple sclerosis (MS). You will have the opportunity to present your work at scientific meetings and publish in peer‑reviewed journals. Your work will contribute to an understanding of how EBV may cause MS and help inform the impact of EBV therapeutics and vaccines on reducing the risk of MS. As a Postdoctoral Research Fellow, you will work with a dedicated mentor team, collaborate internally and externally, and be expected to present your research at scientific conferences. There may be opportunities for project‑related travel, depending on your interest and project needs. Primary Responsibilities Develop statistical models of host and immune response variables predictive of multiple sclerosis in matched case–control studies. Identify and implement analytic methods, such as machine learning or group‑based trajectory models, appropriate for large datasets (>6,000 variables) for exploratory analyses of serology data. Explore external datasets in which findings could be replicated for validation purposes. Collaborate with internal and external scientists to advance the study of immune responses in the relationship between EBV and multiple sclerosis. Evaluate internal and external data sources related to the burden of multiple sclerosis and other autoimmune diseases and their relationship with EBV. Publish results in peer‑reviewed journals and present at scientific conferences. Required Qualifications PhD in epidemiology, biostatistics, infectious diseases, or a related field obtained within 6 months of hire. Strong interest in infectious disease and vaccines. Experience in identifying and implementing appropriate statistical models. Proficiency with analytic software such as R, SAS, or Stata. Excellent written and verbal communication skills. Preferred Qualifications Knowledge of immunology, pharmacoepidemiology, neurology, and/or oncology. Experience with advanced analytic methods, including artificial intelligence and machine learning. Background in molecular epidemiology studies, serology analysis, and omics analyses. Experience using large real‑world healthcare data sources (e.g., insurance or administrative claims data). This is a hybrid position based in West Point, Pennsylvania. Equal Employment Opportunity Statement As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other legally protected characteristics. We are a federal contractor and comply with all affirmative action requirements for protected veterans and individuals with disabilities. #J-18808-Ljbffr Merck & Co.