Posted to MedZilla on 5/23/2017

Takeda Pharmaceuticals

US-MA, Computational Biology Scientist I/II 1700743-MZ


Based in Cambridge, MA, the computational biology scientist will be part of a team focused on bioinformatics and computational biology support of translational and exploratory data analysis across multiple therapeutic areas such as oncology and gastrointestinal diseases. The scientist will apply expertise in bioinformatics and computational biology to analyze various types of molecular profiling and phenotype data to support Takeda discovery and development projects.


  • Serve as computational biology lead for project supports on translational and exploratory data analysis.
  • Performs advanced analysis of DNA-seq, RNA-seq and other sequencing data in combination with publicly available genomics data by applying unsupervised and supervised machine learning algorithms to extract novel and biologically meaningful information.
  • Method development for translational research, e.g. predictive modeling for patient stratification and disease indication selection.
  • Integrates genomics, genetics, epigenetics and literature data to strengthen understanding of diseases and treatment perturbations.
  • Utilizes multiple approaches for analyses of genes, pathways and networks.
  • Writes study reports and presents data effectively in all settings and with participants of all levels of the organization.


  • PhD or equivalent in bioinformatics, computational biology, or a related field, with at least 6 years of bioinformatics experience
  • Very strong programming skills in R, Python, and/or other languages commonly used for bioinformatics analysis. Must be expert in applying major bioinformatics tools.
  • Understands the advantages and limitations of various types of human genetic datasets (e.g. GWAS, CNVs, Rare variants, etc.) and has hands on experience in using public human genetics and epigenetics databases.
  • Has a solid background in basic cellular and molecular biology with an understanding of disease areas like oncology and gastrointestinal diseases.
  • Strong communication and team working abilities to contribute in a team that operates as a unit on large projects.
  • Must be an expert in sequencing data analysis such as RNAseq, DNAseq, scRNA-seq, etc.
  • Must have deep knowledge and working experience to apply advanced machine learning methods such as Hidden Markov Chain, Support Vector Machines, neural nets and deep learning algorithms.
  • Familiarity with text mining algorithms is a plus


  • Carrying, handling and reaching for objects up to 25 lbs.
  • Able to work in a lab environment


  • Some travel to global Takeda sites may be required.
  • Up to 20% travel, both domestic and internationally may be required.

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