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Computational Biologist - Model Systems

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, and 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.

Position description:

Calico is seeking an experienced computational biologist to join a team of scientists investigating aging and age related diseases using a diversity of model systems.

As a member of this team you will lead research projects focused on analyzing molecular and phenotypic data in model organisms including single cell and larger in-vivo models. The projects will involve integrating multiple heterogeneous datasets to construct genome-scale networks, make functional predictions and model biological processes. You will develop new computational methods as well as apply existing tools to examine datasets generated by Calico, Calico’s collaborators and public sources. You will work in close collaboration with experimental scientists, other computational biologists, machine learning experts and software developers. The results of your research will directly impact other scientific directions at Calico and contribute to our long-term mission of improving human health and lifespan.

Position requirements:

  • 5+ years of experience in computational biology, including a PhD degree in biology, computer science, statistics or related fields
  • Strong coding skills in Python, R or Matlab; experience with SQL databases
  • Interest in understanding the biology of simple organisms and transferring knowledge to more complex systems, including humans
  • Track record of completed scientific projects as evidenced by publications and preprints
  • Ability to work with others and to communicate effectively in person and in writing     
  • Strong interest in working on difficult problems as part of a team that thinks and acts positively

 

 

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