The Cell Therapy and Synthetic Immunity group addresses computational challenges associated with

immunotherapies that primarily utilizes cell and gene therapy. The group is seeking a motivated and

detail-oriented Computational Scientist to join the team to address both platform and target biology

related computational needs. This role will interface with a multidisciplinary team of scientists focused

on developing innovative therapies and enhancing our understanding of cellular therapies.

Location

• Remote location in US and Canada OK. Must be available during PST working hours.

Key Responsibilities

• Integrate multi-modal datasets (e.g., scRNA-seq, CITE-seq, spatial transcriptomics) to uncover

insights into tumor micro-environment and immune responses pre/post treatment

• Develop computational approaches to integrate large single cell datasets to generate

reference maps/cell atlases.

• Utilize gene signatures to interpret changes in composition of cell-types and/or their functional

states in longitudinal datasets

• Analyze large genomic datasets (bulk RNA-seq, WGS/WES) to generate data package in

support of target ID/validation

• Assist in designing experimental studies and contribute innovative ideas for improving

workflow efficiency.

Role Requirements

• PhD in Computational Biology, Genomics, Bioinformatics, Immunology, or a related field
• Experience in analyzing single cell genomics data (scRNA-seq, scATAC-seq, spatial omics)
• Strong proficiency with R and/or Python for statistical computing and data visualization
• Familiarity with popular single cell analysis tools (e.g., Seurat, Scanpy, Cell Ranger, Loupe,

etc.)

• Demonstrated ability to work independently on complex data analysis problems and

communicate results clearly to interdisciplinary teams

Preferred Qualifications

• Deep understanding of immune cell biology and ability to interpret immune-related

transcriptional signatures

• Prior experience in analysis of clinical datasets
• Basic understanding of machine learning approaches (LLMs etc.)

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