Job Description

Position Summary:
Seeking a contractor at the level of Senior Scientist to join our Computational Biology team . This individual will work on several attributes of our drug and target discovery pipeline including biomarker discovery in late-stage programs, as well as target ID and mechanism of action research for early-stage programs.  The role will have a heavy focus on computational analysis of internal and public external multi-omics and CRISPR screening datasets to test and help understand the mechanisms of action of drugs in the pipeline.  The ideal candidate will be comfortable working with a range of omics datatypes generated from in vitro and in vivo model systems, and from clinical samples. The ideal candidate will enjoy working collaboratively in a fast-paced environment on a range of challenging and exciting scientific problems. This is a unique opportunity to gain broad computational experience throughout the early stages of drug development and work on cutting edge functional genomic and single cell datasets. What you'll do:

• • Carry out standard and complex differential analyses of omics data amongst a wide array of in vitro, and in vivo samples.
  • Work closely with scientists throughout the organization to accelerate and enable testing of hypotheses through computational analyses
  • Clearly communicate and present results to project teams and the larger organization
  • Develop working knowledge of cancer biology underpinning projects to facilitate communication and more rapid analyses 

• • BS, MS, or PhD in Bioinformatics, Computational Biology, or closely associated field.
  • Hands-on experience with differential gene expression analyses using RNA-Seq.
  • Experience with human NGS datasets and UNIX based bioinformatic tools.
  • Proficiency in Python/R data processing and usage of bioinformatic packages.
  • Experience with visualization and presentation of complex data.
  • Experience with CLI usage of cluster and/or cloud computing resources.
  • Working understanding behind linear modeling, regression techniques, and statistical testing.
  • Experience in using AI models to increase efficiency.
  • Problem solver and self-starter who is passionate about their own career growth and development
  • Team player who is comfortable playing supporting or leading roles when necessary
  • Clear communicator who can work closely with biological scientists

• • Experience with local LLMs or commercial LLM APIs and utilization in workflows.
  • Experience with WGS/WES analyses including mutation calling and variant annotation.
  • Experience handling non-NGS -omic datasets (Mass Spec, Olink, Nanostring, etc).
  • Experience with functional genomics datasets (e.g. CRISPR screening).
  • Experience with Oncology based omics data and data resources such as TCGA and DepMap.
  • Experience building and validating machine learning based models with multi-omic data sources.
  • Experience with non-linear modeling and optimization techniques.
  • Experience with Bayesian methods and causal network modeling.
  • Experience developing interactive UIs with python/R/Javascript.
  • Familiarity with version control and software engineering best practices.

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