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Sr. Computational Biologist I

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Job Description - Sr. Computational Biologist I

Job Details

Sr. Computational Biologist

Join a dynamic interdisciplinary team of bioinformatic scientists, molecular biologists, and software engineers passionate about advancing cancer research and computational biology. This role focuses on developing and applying analytical methods for cutting-edge genomic research to improve patient outcomes.

Key Responsibilities

  • Software Development: Create software to advance single-cell genomics research.
  • Data Analysis: Analyze sequencing datasets to address innovative and clinically relevant research questions.
  • Troubleshooting: Evaluate results and resolve issues with new analytical methods.
  • Research and Application: Explore new developments in computational biology and apply them to large-scale datasets.
  • Collaboration: Partner with researchers to address questions in cancer genomics and interpret results.
  • Training: Mentor junior analysts in running pipelines, performing quality control, and routine analyses.

Key Qualifications

  • Education: PhD in Bioinformatics, Computational Biology, or Computer Science with a focus on molecular biology, or equivalent practical experience.
  • Technical Skills:
    • Proficiency in Linux and programming languages like Python or R.
    • Familiarity with high-throughput sequence data is advantageous.
    • Experience with version control systems such as Git.
  • Portfolio: Demonstrate coding skills through a code sample or portfolio.

Core Skills

  • Motivation: Driven to develop impactful software for advancing scientific discovery.
  • Biological Expertise: Strong interest in molecular and cell biology.
  • Attention to Detail: Skilled in identifying and addressing data anomalies effectively.
  • Collaboration: Adept at working with multidisciplinary teams to provide research-focused solutions.
  • Decision-Making: Strong ability to make timely and effective decisions.
  • Resilience: Capability to overcome challenges and adapt to new situations.
  • Learning Agility: Quick to apply knowledge from past experiences to new opportunities.
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