Job Description

Sr. Research Associate, Genetic Pharmacology (Translational Science)

Location: Onsite – Belmont, CA

Contract Length: 6-months

Position Overview:

Looking for a highly motivated Senior Research Associate with a strong background in data science and computational biology to join our translational research team. This role focuses on developing and applying tools that turn complex biological data into actionable insights for cancer research. The ideal candidate will contribute to building robust analytics platforms, statistical models, and informatics systems that support early-stage therapeutic discovery and development. Prior experience with LIMS platforms (especially Benchling), interactive data visualization (e.g., RShiny), and handling high-throughput genomic data is especially valuable.

Key Responsibilities:

Bioinformatics & Analytics:

• Perform quality control and analyze next-generation sequencing data, including functional genomics screens, targeted amplicon sequencing, whole-exome/genome sequencing (WES/WGS), bulk and single-cell RNA-seq, and spatial transcriptomics.
• Design and apply computational methods for biomarker identification, therapeutic response prediction, and patient stratification in oncology-focused studies.
• Collaborate with multidisciplinary teams to structure, integrate, and visualize diverse biological datasets.

Tool & Pipeline Development:

• Develop and maintain scalable, automated data analysis pipelines.
• Define and build user-centric applications for data exploration and visualization.
• Deliver intuitive analytical tools that enhance decision-making across research functions.

LIMS & Data Infrastructure:

• Extend and manage LIMS systems (e.g., Benchling) to organize experimental workflows, biological assets, and data tracking.
• Drive initiatives to improve data standardization, accessibility, and governance in line with FAIR principles.

Project Coordination & Collaboration:

• Engage with research and technical teams to identify data analysis needs and optimize workflows.
• Lead small-scale analytics projects from concept to implementation.

Qualifications & Background:

Required:

• Master’s degree in a quantitative field (Bioinformatics, Computational Biology, Biomedical Engineering, Biostatistics, etc.) with 1+ years of experience, or a Bachelor’s degree with 5+ years in a relevant oncology-focused research setting.
• Strong coding skills in Python and R for statistical analysis and data visualization.
• Proven experience with interactive web applications for data analysis (e.g., RShiny, Dash).
• Hands-on experience with bioinformatics platforms such as Benchling, DNANexus, or Rosalind.
• Demonstrated ability to integrate, analyze, and visualize large-scale biological data sets.
• Strong knowledge of statistical modeling applied to biological data.
• Effective communicator and team collaborator in a fast-paced, cross-functional environment.

Preferred:

• Experience in developing data models and entity schemas within LIMS platforms, especially Benchling.
• Background in biomarker research—prognostic and predictive—in oncology.
• Familiarity with analyzing data from cancer-focused models including cell lines, organoids, or patient-derived tumor samples.

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