Translational Medicine Computational Biologist

Job Location: 
Cambridge, MA
Job Description: 

We seek an experienced bioinformatics scientist / computational biologist to work with therapeutics groups across the sanofi families of companies in Boston.

As an part of scientific teams identifying both targets and patient selection biomarkers, you will
- Develop analysis and quality control pipelines for a variety of Next Generation Sequencing (NGS) applications such as DNA-seq, ChIP-seq, and RNA-seq
- Develop novel statistical methods for indel, SNP, genotype, fusion and complex variant calling on a variety of internal and external sequencing platforms (454, SOLID, Illumina, PacBIO, etc.)
- Design the strategy for sequencing outsourcing as well as sequencing workflow data management and the computing infrastructure for processing NGS data (local vs. Amazon cloud, etc.)
- Develop Translational Medicine plans (e.g., patient selection and indication biomarkers) in collaboration with Translational and Experimental Medicine project teams
Supply any computational, statistical, machine learning or modeling capability needed to synthesize data into the actionable next steps for the Projects

Educational requirements:
- Ph.D. in a computational, statistical, biophysics, or bioinformatics related fields
- A minimum of 5-years research (academia or industry) experience

Knowledge requirements

An ideal candidate will be collaborative, self-directed and possess:
- First-hand experience in NGS analysis, methods, and data management
- First-hand multi-parametric data mining experience on expression, copy number and profiling datasets for target identification and biomarker discovery. For example, multivariate analysis; dimensionality reduction methods; parametric and non-parametric statistical methods; Bayesian statistics; pattern recognition or classification methods.
- First-hand experience at integrating publicly or commercially available genetic, genomic, and interaction datasets with novel experimental data to identify testable hypotheses
- Statistical programming skills like SAS/S-plus, R/bioconductor and pipeline pilot or equivalents
- A background in Oncology, Rare Diseases, Vaccines, Translational Research, Pathway Analysis, Quantitative Methods for Systems Biology, Network Analysis, or Simulation are a plus.

Required Key Attributes:
- Positive, proactive can-do mindset
- Demonstrated ability to lead projects of moderate scope, mapping-out critical path, milestones and timelines, as well as manage customer expectations with minimal supervision
- Developed communication and presentation skills and a successful track record of collaborating with cross-functional scientific teams


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