Computational Biologist/Research Scientist

Seattle, WA
Includes full health/welfare benefits, retirement plan, paid time off
November 16 2018
Position Type
Full Time
Organization Type

The Baliga Lab is seeking an enthusiastic and talented scientist to join a leading edge effort to use systems biology to drive rational drug discovery. Candidates will be considered at postdoctoral, research scientist, or senior scientist level, depending on their prior experience. The position offers an exciting opportunity to contribute towards finding therapies against tuberculosis, a growing global health threat. The scientist will work closely with a multidisciplinary team of scientists to derive knowledge from large, multiomics datasets to predict novel drug combinations against Mycobacterium tuberculosis (MTB). The aim of this project is to predict drug synergy using machine learning, and other integrative approaches, on large-scale gene expression profile datasets. The strategy, which builds on extensive prior work in the Baliga Lab, will involve the application and development of gene regulatory network inference algorithms to uncover mechanisms operating across scales from a molecular to a systems level that enable MTB tolerance and resistance to current standard therapies. Computational predictions of these mechanisms will drive experimentation to discover novel interventions to improve therapy. The position offers an extraordinary team-based science environment with opportunities for significant growth, training and career advancements.

Job responsibilities will include:

  • Develop new computational tools and methods to analyze and integrate biological data from large datasets to derive new knowledge.

  • Perform analyses in a accessible manner and to clearly communicate analysis results and methods with collaborating researchers who may not have computational backgrounds.

Required education/experience:

  • Ph.D. in bioinformatics, biology, bioengineering, computational biology, or a related scientific discipline.

  • Background in infectious disease is not required for this position. However, enthusiasm and interest in learning about infectious disease and other biological systems is essential.

Required skills:

  • Excellence in using and developing machine learning methods.

  • Excellence in high-dimensional data analysis, e.g., gene expression profiles.

  • Deep understanding of gene regulatory mechanisms in the context of genotype-to-phenotype mapping, preferably in bacterial systems.

  • Strong analytical, programming, and communication skills.

  • Advanced knowledge of  bioinformatics tools, methods and data resources.

  • Excellence in employing a variety of programming languages (Python, R and MATLAB) and tools to bridge information from different sources.

  • Excellence in code documentation and version control systems.

  • Experience with code debugging/rewriting and incorporation of new functionalities  that interact with a variety of other tools, data resources, APIs, etc.

  • Ability to collaborate with biologists and software engineers to leverage models and analytical workflows to support integrative data approaches.

  • Experience developing computational tools to make analysis results easily interpretable and accessible to other researchers.

  • Knowledge of using parallel computing environments.

  • Motivation to explore data with careful attention to detail.