Rangam
RCI-GILD-16710 Associate Scientist – single-cell RNA Bioinformatics III (Oncolo
Rangam, Santa Monica, California, United States, 90403
RCI-GILD-16710 Associate Scientist – single-cell RNA Bioinformatics III (Oncology) – Santa Monica, CA
Position Summary
We are seeking a highly motivated Associate Scientist in Bioinformatics to support the development of novel cell therapies. This role will be integral to our NGS & functional genomics efforts, focusing on the analysis and interpretation of complex datasets to drive decision‑making in therapeutic programs.
The ideal candidate will have strong hands‑on
experience with Illumina sequencing data analysis, single‑cell RNA‑seq, and operational lab informatics systems (Benchling, LIMS), coupled with foundational knowledge of microbiology and immunology in the context of cancer.
Key Responsibilities
Process, analyze, and perform quality control (QC) for a variety of NGS datasets, primarily single‑cell RNA sequencing (scRNA‑seq) and bulk RNA‑seq from clinical and research samples.
Execute, optimize, and troubleshoot bioinformatics pipelines for scRNA‑seq, targeted gene panels, whole exome/transcriptome sequencing, and other genomic assays.
Perform standard NGS analyses: FASTQ QC, alignment, variant calling, gene expression quantification, differential expression, and cell population clustering/annotation.
Utilize Benchling for electronic lab notebook (ELN) functions and sample/data tracking.
Work within the Laboratory Information Management System (LIMS) to manage sample metadata, track workflow status, and ensure data integrity.
Collaborate closely with bench scientists in sequencing, genomics, and immunology to design experiments, interpret results, and support data‑driven decisions for cell therapy development.
Maintain reproducible analysis code and workflows using version control (Git) and standard bioinformatics tools in a Linux environment.
Prepare clear documentation, QC reports, and presentation‑ready analysis summaries for team and stakeholder review.
Contribute to SOP development and continuous improvement of computational and data management workflows.
Required Qualifications
Bachelor’s degree in Microbiology, Immunology, Molecular Biology, or a closely related life science field is required. A Master’s degree in Bioinformatics, Computational Biology, or a related field is a strong plus.
2+ years of relevant experience (with BS) or 1+ year (with MS) in bioinformatics analysis, specifically with Illumina NGS data.
Demonstrated hands‑on experience with single‑cell RNA‑seq data analysis (e.g., using tools like Cell Ranger, Seurat, Scanpy).
Proven experience using Benchling (ELN) and a Laboratory Information Management System (LIMS) in a production or research environment.
Proficiency in R and/or Python for statistical analysis, data visualization, and pipeline scripting.
Strong command‑line skills in a Linux/Unix environment and experience with NGS tools (e.g., FastQC, STAR/BWA, samtools, bcftools, MultiQC).
Solid understanding of sequencing metrics, QC principles, and data integrity.
Excellent communication skills with the ability to convey technical results to interdisciplinary teams.
Preferred Qualifications
Knowledge of cancer biology, immunology, or immuno‑oncology.
Experience with workflow managers (e.g., Nextflow, Snakemake).
Familiarity with immunogenomics analysis (TCR/BCR repertoire).
Exposure to regulated (CLIA/GxP) environments and documentation practices.
Experience working in a cloud (AWS, Google Cloud) or high‑performance computing (HPC) cluster environment.
Seniority Level Mid‑Senior level
Employment Type Contract
Job Function Science
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We are seeking a highly motivated Associate Scientist in Bioinformatics to support the development of novel cell therapies. This role will be integral to our NGS & functional genomics efforts, focusing on the analysis and interpretation of complex datasets to drive decision‑making in therapeutic programs.
The ideal candidate will have strong hands‑on
experience with Illumina sequencing data analysis, single‑cell RNA‑seq, and operational lab informatics systems (Benchling, LIMS), coupled with foundational knowledge of microbiology and immunology in the context of cancer.
Key Responsibilities
Process, analyze, and perform quality control (QC) for a variety of NGS datasets, primarily single‑cell RNA sequencing (scRNA‑seq) and bulk RNA‑seq from clinical and research samples.
Execute, optimize, and troubleshoot bioinformatics pipelines for scRNA‑seq, targeted gene panels, whole exome/transcriptome sequencing, and other genomic assays.
Perform standard NGS analyses: FASTQ QC, alignment, variant calling, gene expression quantification, differential expression, and cell population clustering/annotation.
Utilize Benchling for electronic lab notebook (ELN) functions and sample/data tracking.
Work within the Laboratory Information Management System (LIMS) to manage sample metadata, track workflow status, and ensure data integrity.
Collaborate closely with bench scientists in sequencing, genomics, and immunology to design experiments, interpret results, and support data‑driven decisions for cell therapy development.
Maintain reproducible analysis code and workflows using version control (Git) and standard bioinformatics tools in a Linux environment.
Prepare clear documentation, QC reports, and presentation‑ready analysis summaries for team and stakeholder review.
Contribute to SOP development and continuous improvement of computational and data management workflows.
Required Qualifications
Bachelor’s degree in Microbiology, Immunology, Molecular Biology, or a closely related life science field is required. A Master’s degree in Bioinformatics, Computational Biology, or a related field is a strong plus.
2+ years of relevant experience (with BS) or 1+ year (with MS) in bioinformatics analysis, specifically with Illumina NGS data.
Demonstrated hands‑on experience with single‑cell RNA‑seq data analysis (e.g., using tools like Cell Ranger, Seurat, Scanpy).
Proven experience using Benchling (ELN) and a Laboratory Information Management System (LIMS) in a production or research environment.
Proficiency in R and/or Python for statistical analysis, data visualization, and pipeline scripting.
Strong command‑line skills in a Linux/Unix environment and experience with NGS tools (e.g., FastQC, STAR/BWA, samtools, bcftools, MultiQC).
Solid understanding of sequencing metrics, QC principles, and data integrity.
Excellent communication skills with the ability to convey technical results to interdisciplinary teams.
Preferred Qualifications
Knowledge of cancer biology, immunology, or immuno‑oncology.
Experience with workflow managers (e.g., Nextflow, Snakemake).
Familiarity with immunogenomics analysis (TCR/BCR repertoire).
Exposure to regulated (CLIA/GxP) environments and documentation practices.
Experience working in a cloud (AWS, Google Cloud) or high‑performance computing (HPC) cluster environment.
Seniority Level Mid‑Senior level
Employment Type Contract
Job Function Science
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