Who we are:
Calico is a research and development company whose mission is to harness advanced technologies to increase our understanding of the biology that controls lifespan. We will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Executing on this mission will require an unprecedented level of interdisciplinary effort and a long-term focus for which funding is already in place.
Calico is seeking a computational scientist with deep knowledge of, and extensive experience in, biostatistical analysis of human health records and large clinical databases in order to gain insight into the biology of human disease. The ideal candidate will have a track record of creative problem solving, an ability to develop and apply complex statistical and algorithmic modeling techniques, and a passion for using these approaches to advance our fundamental understanding of the human biology and disease. Responsibilities will include the implementation of statistical models to define the physiology of the aging process and to assist with the interpretation and integration of large phenotypic datasets (including metabolomics, proteomics, and lipidomics) with the intent to identify causal biomarkers. The successful candidate will interaction with cross-functional teams to assist with the analyses of experimental data, theoretical exploration of analytical methods, as well as the implementation of custom software to perform these analyses.
Applicants must have either a Ph.D. in computational biology, statistics, mathematics with previous exposure to biological data analysis, or in PH.D. in biological sciences (or related discipline) with a very strong record of computational data analysis; or, a similar M.S. with 6+ years of additional relevant experience. Candidate must be very proficient in programming in at least one structured programming language ( C, C++, python) and must have extensive experience working with R. We are looking for an enthusiastic team player with a passion for tackling complex biological questions with excellent verbal/written communication skills.