Pfizer’s Rare Disease Research Unit (RDRU) is dedicated to the development of novel therapeutics for orphan diseases. The recent and rapid emergence of large databases of genotype/phenotype data has led to many new and exciting opportunities for human genetics to advance rare disease drug development projects. The RDRU Integrative Biology team is searching for a computational geneticist with a deep passion for extending our understanding of the genetics of rare disease and translating these insights into novel therapeutics. As a member of our Integrative Biology team located in Cambridge, Massachusetts, you will be responsible for designing and delivering analyses that incorporate both proprietary and public genetics and other ‘omics datasets for target discovery and target validation. You will work with laboratory biologists, computational biologists, geneticists, and statisticians within the RDRU and across the broader Pfizer community in a highly collaborative environment to deliver impactful and actionable insights from human genetics. A successful candidate will also be comfortable working with external collaborators from industry and academia to advance our understanding of the genetics of rare disease.
•Background in biological and/or quantitative sciences; PhD in genetics, statistical genetics, or a related field with 0-3 years relevant experience
•Sound statistical and quantitative skills with knowledge of epidemiological principles and population-based research.
•Familiarity with WGS/WES analysis, variant annotation and key genetics databases such as gnomAD
•Proficiency in programming, scripting, querying and statistical analysis languages such as R, Python, Perl, SQL
•Proficiency in standard methods for reproducible research such as Jupyter notebooks or Rmarkdown
•Deep desire to understand biological and pathological processes that lead to human disease
•Excellent communication, interpersonal, and presentation skills
•Background in human biology/medicine with some knowledge of pathophysiology in the areas of neurologic, hematologic or metabolic disease is highly preferred
•Understanding of methodology specific to the genetics of rare disease
•Track record of innovative and impactful research in genetics including peer-reviewed publications
•Experience analyzing large genetics datasets and integrating additional data types to further clinical and biological understanding
•Experience analyzing data from at least one other ‘omics technology such as transcriptomics, proteomics, lipidomics, metabolomics or epigenomics
•Ability to multi-task and prioritize amongst competing time-sensitive projects
•Strong desire to continually learn new skills