Posted to MedZilla on 6/25/2017

Takeda Pharmaceuticals

US-CA, Computational Biologist - Discovery Toxicology 1601922-MZ



  • Design, implement and execute state-of-the-art bioinformatic tools for the collection, curation, analysis, mining and visualization of complex biological data
  • Identify pharmacological mechanisms and adverse outcome pathways that are related to the observation of in vivo toxicity, and propose actionable and testable solutions
  • Enable the design and selection of high-quality drug candidates through the identification of project-related safety liabilities and application of validated in silico and in vitro tools


  • Integrate into early discovery project teams, assist in the identification of on- and off-target pharmacology risks and identify de-risking strategies
  • Develop and apply bioinformatic tools to assist in the curation, analysis and visualization of large-scale, complex toxicological datasets from multiple sources
  • Work collaboratively on computational projects across multiple disciplinary areas, including DMPK, medicinal chemistry, drug safety and pharmacology
  • Design new computational biology tools and applications that are relevant to the design of drugs with the safest pharmacological profile
  • Drive the improvement of early risk assessment strategies through the identification of toxicological pathways that are applicable across all therapeutic areas
  • Develop and maintain global platforms that integrate internal and external bioinformatic tools and models



  • PhD in computational biology, bioinformatics or equivalent
  • Passion to decrease safety related attrition in drug discovery
  • Demonstrated experience in data curation, data mining and an ability to interrogate, interpret, and visualize large and diverse, biological and toxicological datasets
  • Demonstrated ability to independently develop and implement computational workflows starting from raw data through analysis, hypothesis generation and visualization
  • Understanding of all aspects of drug discovery including cell and molecular biology, medicinal chemistry and basic principles of drug pharmacokinetics and metabolism
  • Demonstrated experience in leveraging in silico methodologies to drive drug discovery projects
  • Familiarity with proteomic and genomic data analysis and systems biology software
  • Experience with programming and scripting languages (e.g. Perl, C/C++, Java, R, Python)
  • Demonstrated experience and ability to work effectively in a matrix, global environment as part of a multidisciplinary team
  • Skilled in clearly communicating complex computational approaches and methodology to non-computational scientists
  • Pre-clinical or clinical drug safety experience is desirable
  • Strong, written, oral communication and influencing skills are essential


  • Typical office base

  • 10%, both domestic and international possible

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