The Regeneron Genetics Center (RGC) is a wholly-owned subsidiary of the Company, whose goals are to apply large scale human genetics to identify new drug targets and to guide the development of therapeutics programs and precision medicine. Building upon Regeneron's strengths in mouse genetics and genetics-driven drug discovery and development, the RGC specializes in ultra-high-throughput exome sequencing, large scale informatics and data analysis encompassing genomics and electronic health records, and translating genetic discoveries into new biology and drug discovery opportunities. The RGC leverages multiple approaches including large population based studies, Mendelian genetics and family based studies, founder population genetics, and large-scale disease focused projects and has developed a network of over 50 collaborations with research organizations around the world. Including some of the largest sequencing studies in the world, such as the DiscovEHR study in collaboration with Geisinger Health System, and an initiative to sequence 500,000 participants with the UK Biobank, the RGC has built one of the largest human genetics databases, including sequence data from over several hundred thousand participants and rapidly growing. Our interests encompass a breadth of different areas across all therapeutic areas and the RGC is highly integrated into all facets of research and development at Regeneron. Program goals include target discovery, indication discovery, and patient-disease stratification. Objectives include advancing basic science around the world through public sharing of discoveries, providing clinically-valuable insights to physicians and providers of collaborating health-care systems, improving patient outcomes, and identifying novel targets for drug development.
Contribute to the methods development, analysis and interpretation of 100,000s of genotyped and sequenced humans, with the goal of making scientific discoveries and generating the knowledge that will enable Regeneron to deliver better medicines to the patients who need them. Work collaboratively with other experts in statistical genetics, genomic data analysis, biology, computation and medicine to develop, design, execute and refine analyses and methods that connect genetic variation to human diseases and health and help develop and implement the methods and tools that will enable these analyses to be executed and interpreted at scale.
• The candidate should have a strong background in statistical theory, developing statistical methodology, familiarity with analytical approaches and challenges in modern human genetics and genomics, or with statistical computing in another data-rich field.
• Knowledge of modern human genetics and genomics could be demonstrated by understanding and practical experience of genomewide association, sequencing studies, heritability estimation, detection of interactions, techniques for modeling population structure and ancestry, mendelian randomization and/or analysis of polygenic risk scores.
• Knowledge of modern statistical computing could be demonstrated by understanding of generalized linear mixed models, techniques for Bayesian computing (such as MCMC and Variational Bayes), understanding of machine learning and survival analysis, and methods and tools for data visualization.
• Critically review and provide feedback on analysis plans, results and summaries to ensure they are accurate and reliable. Identify potential problems and propose remedies or refinements.
• Outstanding communication skills and an ability to summarize and present the results of human genetic studies to a variety of technical audiences, ranging from experts in statistical genetics and computation to experts in biology, drug design and medicine. The candidate would be expected to contribute to publications on scientific findings as and when appropriate.
• Ability to work in a highly interactive environment with a diverse team of colleagues. Provide mentorship and guidance to more junior colleagues to help them develop their full potential and build new skills and abilities.
• Knowledge of genomewide analyses and approaches, including quality control options for genomic data, approaches for association analysis in the presence of relatedness or population structure, and approaches for burden based analyses. Understanding of strategies and methods for genotype imputation, haplotyping, relationship inference and/or polygenic risk score estimation.
• Strong knowledge of statistical theory and experience of developing statistical methodology, ideally in the field of statistical genetics.
• Experience with multiple tools for large scale genetic analyses (e.g. PLINK, EPACTS, SAIGE, minimac, IMPUTE, SNPTEST, METAL/RAREMETAL).
• Ability to summarize and distil results concisely. Excellent oral presentation and writing skills.
• Expertise with the analysis of DNA sequence data is a plus.
• Expertise in developing analysis packages and tools is highly desired, as demonstrated by leadership or contributor roles to statistical packages available on GitHub or elsewhere.
• 2-3 years of experience post-PhD expected.
This is an opportunity to join our select team that is already leading the way in the Pharmaceutical/Biotech industry. Apply today and learn more about Regeneron's unwavering commitment to combining good science & good business.
To all agencies: Please, no phone calls or emails to any employee of Regeneron about this opening. All resumes submitted by search firms/employment agencies to any employee at Regeneron via-email, the internet or in any form and/or method will be deemed the sole property of Regeneron, unless such search firms/employment agencies were engaged by Regeneron for this position and a valid agreement with Regeneron is in place. In the event a candidate who was submitted outside of the Regeneron agency engagement process is hired, no fee or payment of any kind will be paid.
Regeneron is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability status, protected veteran status, or any other characteristic protected by law.