Bioinformatics Scientist

LUNDQUIST INSTITUTE FOR BIOMEDICAL INNOVATION AT HARBOR-UCLA•Torrance, CA

1d•$75,000 - $85,000•Onsite

About The Position

The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center (TLI) is Los Angeles County's preeminent independent, not-for-profit biomedical research hub, excelling in transforming scientific breakthroughs into practical therapies. With a $90 million annual budget, TLI is home to over 150 investigators and 500 staff, advancing 600 projects in areas such as Infection and Immunity, Cancer, and Women's Health. Founded in 1952, the Institute continues to train physician-scientists and manage healthcare programs for 60,000 underserved families throughout South Los Angeles. The Bioinformatics Scientist leads advanced computational and bioinformatics analyses supporting cancer and translational research initiatives. This position develops and applies state-of-the-art analytical approaches to next-generation sequencing (NGS) and multi-omics datasets, integrating diverse genomic, transcriptomic, epigenomic, spatial sequencing, and related biological data. The Bioinformatics Scientist collaborates closely with investigators, laboratory personnel, statisticians, and external collaborators to generate meaningful scientific insights, advance research objectives, and contribute to high-impact publications and presentations. The role requires staying current with emerging computational methodologies, bioinformatics tools, and artificial intelligence applications relevant to biomedical research.

Requirements

PhD in Bioinformatics, Computational Biology, Genomics, Biostatistics, Biomedical Informatics, Computer Science, or a closely related quantitative discipline.
More than three years of relevant postdoctoral or post-PhD experience in bioinformatics, computational biology, genomics, cancer research, or related fields.
Demonstrated expertise in NGS and multi-omics data analysis.
Strong record of scientific contributions, including multiple peer-reviewed publications involving cancer genomics or omics research.
Experience conducting cancer-related genomic, transcriptomic, epigenomic, and other omics analyses.
Experience accessing, curating, and analyzing public annotated genomic and NGS databases.
Understanding of spatial sequencing technologies, spatial transcriptomics, associated protocols, and analytical approaches.
Proficiency in R and familiarity with additional bioinformatics software tools, statistical packages, and computational workflows.
Experience developing and implementing analytical pipelines and computational methods.
Strong knowledge of biostatistical methodologies and their application to biological datasets.
Ability to evaluate, implement, and optimize emerging computational technologies and analytical programs.
Ability to communicate complex scientific findings through publications, presentations, and collaborative discussions.
Excellent analytical, organizational, problem-solving, and scientific communication skills.
Demonstrated ability to work effectively in multidisciplinary collaborative research environments.

Nice To Haves

Experience supporting translational, clinical, precision medicine, or cancer research programs.
Experience with cloud computing and high-performance computing environments.
Experience applying machine learning and artificial intelligence methods to biological datasets.
Experience mentoring junior scientists, bioinformatics analysts, or trainees.
Experience leading collaborative multi-institutional research initiatives.

Responsibilities

Lead the analysis and interpretation of next-generation sequencing (NGS) and multi-omics datasets, including genomic, transcriptomic, epigenomic, and related biological data.
Design, develop, validate, and implement computational workflows and bioinformatics pipelines to support cancer and translational research studies.
Perform advanced analytical assessments of omics datasets and identify biologically meaningful patterns, biomarkers, molecular signatures, and disease-related mechanisms.
Access, curate, and analyze publicly available annotated genomic, transcriptomic, and cancer-related databases.
Analyze and interpret spatial sequencing and spatial transcriptomics datasets and understand associated laboratory protocols and analytical methodologies.
Employ and evaluate emerging computational technologies, algorithms, and analytical software for NGS and multi-omics applications.
Apply biostatistical methods using R and other established bioinformatics software platforms.
Utilize artificial intelligence and machine learning methodologies to enhance bioinformatics and data-analysis workflows when appropriate.
Collaborate with laboratory personnel, investigators, clinicians, biostatisticians, and external collaborators to define analytical objectives and interpret research findings.
Generate publication-quality figures, tables, datasets, methods descriptions, and analytical reports.
Contribute to peer-reviewed manuscripts, scientific presentations, abstracts, grant applications, and other scholarly communications.
Maintain organized and reproducible analytical workflows, documentation, code repositories, and data-management practices.
Stay current with advances in bioinformatics, computational biology, NGS technologies, omics analytics, artificial intelligence, and related scientific disciplines.
Perform other duties as assigned in support of research and institutional objectives.