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Bioinformatics Analyst II

companyRandstad Life Sciences US
locationCambridge, MA, USA
PublishedPublished: 6/14/2022
Full Time

Bioinformatics Analyst II

1 year

Cambridge, MA (Hybrid)

Summary

  • Immunology team is expanding its early discovery team, focusing on identifying new targets for autoimmune and chronic inflammatory diseases. We are looking for a motivated and talented individual to join us as a Computational Scientist. In this role, you will contribute to computational analyses that predict drug responses using high-throughput molecular profiling data and support the discovery of new therapeutic targets using high-throughput molecular profiling data.

Key Responsibilities:

  • Build a Single-Cell Atlas: Utilize publicly available single-cell datasets to build comprehensive single-cell atlases, enhancing our understanding of cellular heterogeneity in immune system and disease contexts.
  • Analyze Single-Cell Data: Assist in the analysis of single-cell RNA-seq, TCR-seq, and BCR-seq data to identify disease-associated regulatory networks and biomarkers.
  • Support Multi-Omics Integration: Help integrate various omics data (e.g., gene expression, proteomics) to gain insights into disease mechanisms and identify potential drug targets.
  • Develop Machine Learning Models: Contribute to the development and implementation of machine learning models for data analysis and target identification.
  • Communicate Findings: Support the team in interpreting results and presenting scientific data to both internal and external stakeholders.
  • Collaborate with Teams: Work with cross-functional teams to leverage computational methods in therapeutic development.

Basic Qualifications:

  • Bachelors or Masters degree in bioinformatics, computer science, computational biology, or a related field.
  • Some experience in a relevant academic or industry setting is preferred.
  • Proficiency in programming languages, particularly Python, with a solid understanding of data analysis and visualization techniques.
  • Familiarity with omics data types (e.g., RNA-seq) and basic machine learning concepts.
  • Strong problem-solving skills and a desire to learn.

Preferred Qualifications:

  • Exposure to immunology or experience with biological data analysis.
  • Familiarity with cloud computing and data management environments.
  • Collaborative work style and effective communication skills.
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