Senior Scientist - siRNA Design & Off-Target Analysis

AbbVie

Worcester (MA)

On-site

USD 120,000 - 170,000

Full time

47 hours ago
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Benefits offered by this job

Paid time off
Medical/dental/vision insurance
401(k) plan
Short-term incentive programs

Job summary

AbbVie in Worcester, MA is seeking a Senior Scientist with deep expertise in computational biology, molecular design, and next‑generation sequencing to drive siRNA design and off-target assessment. You will establish and optimize siRNA sequences, develop off-target workflows, and integrate transcriptomic and genomic data to advance safer RNA-based therapeutics.

The role requires strong biological insight, quantitative skills, and the ability to build reproducible pipelines in Python or R,

Qualifications

  • Advanced coursework or experience in computational biology, genomics, or RNA biology.
  • Proficiency in Python and/or R with reproducible workflows.
  • Experience supporting off-target analysis or risk assessment for RNA-based modalities.

Responsibilities

  • Design and optimize siRNA sequences and pipelines using genomic and transcriptomic data.
  • Develop machine learning models to improve sequence selection.
  • Collaborate on NGS library prep for off-target analysis and integrate data for safety assessments.
  • Translate transcriptomic findings into actionable biological insights.
  • Develop reusable analysis tools and documentation in Python, R, or similar languages.

Skills

Python
R
Data analysis

Education

PhD in computational biology or genomics

Tools

NGS library preparation

Job description

AbbVie in Worcester, MA is seeking a Senior Scientist with deep expertise in computational biology, molecular design, and next‑generation sequencing to drive siRNA design and off-target assessment. You will establish and optimize siRNA sequences, develop off-target workflows, and integrate transcriptomic and genomic data to advance safer RNA-based therapeutics.

The role requires strong biological insight, quantitative skills, and the ability to build reproducible pipelines in Python or R,

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