Computational Biologist, Epidemiology

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico's highly innovative technology labs, its commitment to curiosity-driven discovery science, and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description:

Calico is seeking a computational biologist interested in integrating biobank-scale multi-omics datasets, building models of physiological systems, and developing interventional hypotheses to slow down the aging process. The ideal candidate will have a strong background in biological sciences and experience modeling large-scale human datasets. A desired skill set includes expertise in any of the following: developing and applying causal inference methods, Bayesian networks, ODE/dynamic systems, and integrative multi-omics modeling approaches. Critically, we are looking for a scientist with broad knowledge of both biology and computation, excellent communication skills, and genuine excitement to take on the challenge of modeling aging processes.

Responsibilities:

• Analyses of large-scale biomarker datasets (phenomics, proteomics, metabolomics, and lipidomics)

• Integration of multi-omics data across all layers of biology from genetics through disease outcomes

• Implementation of epidemiological models to define the physiological process involved in aging to identify causal pathways for intervention studies

• Assisting others in interpreting findings and in formulating and testing hypotheses so as to help us develop targeted therapeutics

Position Requirements:

• Ph.D. degree in computational biology or a related area (bioinformatics, systems modeling, statistics, epidemiology)

• Strong statistical skills and training in biological sciences, with a track record of impactful publications

• Proficiency in at least one programming language (Python, R, C++, C)

Nice to Have:

• Practical postdoctoral experience in applying computational modeling to biological processes

• Experience applying and developing causal inference methods

The estimated base salary range for this role is $119,000 - $126,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.