Career Opportunities in the Foresite Capital Network

Job Summary

We are looking for a Computational Biologist with deep expertise in comparative genomic analysis. This candidate will implement novel and open-source computational methods to fuel LifeMine’s fungal genome mining engine. The candidate will work closely with other Genomics’ team members to improve methods for genomic discovery and prioritization of biosynthetic gene clusters.

Job Responsibilities

• Develop and implement novel algorithms for the comparative analysis of fungal genomes
• Construct and interpret phylogenetic trees based on whole genome
• Proactively evaluate new technologies and methods, keep up with current literature, and incorporate new knowledge into the genome analysis pipelines
• Collaborate with other scientists in the Genomics group and other groups at LifeMine
• Summarize findings and present results to collaborators

Job Requirements

• Ph.D. (or M.Sc. with 5+ years of relevant experience) in Computational Biology, Bioinformatics, or Microbial Genomics
• Demonstrated success in applying open source software and in developing novel algorithms for the comparative analysis of genomes
• Deep understanding of phylogenetic analyses and comparative genomics methods, and the ability to computationally traverse phylogenetic trees
• Fluent in major scripting languages such as Python or Perl, and proficient in using the command line in Unix environments
• Previous experience in applying comparative genomics in the field of natural product discovery or an understanding of secondary metabolite biosynthesis is highly desirable
• Experience in applying machine learning algorithm or statistical methods to loving biological problems is desirable
• Demonstrated understanding of relevant public genomic databases
• Ability to work effectively in a multidisciplinary team, and communicate results clearly to management
• Excellent organizational skills
• A sense of adventure and excitement to be part of the development of a new drug discovery paradigm