Scientist I, Computational Biology

eGenesis · Cambridge

Company

eGenesis

Location

Cambridge

Type

Full Time

Job Description

COMPANY MISSION

At eGenesis, we aspire to deliver safe and effective human transplantable cells, tissue and organs utilizing the latest advancements in genome editing. 


POSITION SUMMARY

eGenesis is seeking a highly skilled and motivated Scientist I, Computational Biology, to join our team of scientists in advancing our mission to make xenotransplantation a reality. The ideal candidate will have a robust background in gene editing, genomics and a demonstrated ability to analyze diverse NGS datasets including short- and long-read sequencing technologies (Illumina, PacBio, Nanopore). This individual will play a crucial role providing insights into gene edited product and contributing to our overall development efforts. The ideal candidate should be exceptionally detail-oriented, with strong analytical skills, ensuring high standards of accuracy and efficiency in a dynamic, results-oriented environment. This role offers a unique opportunity to gain experience in a Good Manufacturing Practices (GMP) setting and to be at the forefront of pioneering xenotransplantation.

PRIMARY RESPONSIBILITIES

  • Conduct on-target and off-target data analysis and interpretation
  • Visualization of genomics, transcriptomics, and epigenomics datasets
  • Collaborate with cross-functional teams of scientists to design and execute experiments, integrate computational methods into development projects, and provide data-driven insights
  • Assist in data organization, management, and maintenance to ensure data integrity
  • Stay updated on the latest advancements in computational biology and genomics to implement best practices

QUALIFICATIONS

  • A master's degree with 2-3 years of experience in bioinformatics, computational biology, engineering, computer science, or a related quantitative field
  • A strong ability to program with bash, R and Python
  • Hands-on experience with WGS and/or WES data analysis, variant calling including small variants and complex structural variants
  • Experience with assay development and quality control environments is preferred
  • Strong organization skills and meticulous attention to detail
  • Maintain accurate, up-to-date documentation of work and code
  • Experience with AWS cloud computing, GitHub, Benchling and/or SevenBridges data analysis platform is a plus
  • Knowledge of molecular biology and gene editing is preferred
  • Strong oral and written communication skills
Apply Now

Date Posted

09/09/2024

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