Assistant Research Professor - Genomic Data Analysis

Join the forefront of groundbreaking research at the Beckman Research Institute of City of Hope, where we're changing lives and making a real difference in the fight against cancer, diabetes, and other life-threatening illnesses. Our dedicated and compassionate faculty and staff are driven by a common mission: Contribute to innovative approaches in predicting, preventing, and curing diseases, shaping the future of medicine through cutting-edge research.

An Assistant Research Professor role is available in the lab of Dr. Larry Kwak. You will apply state of the art genomic data analysis techniques to support various user projects dedicated to the Toni Stephenson Lymphoma Center at City of Hope. You will be expected to develop innovative workflow to apply bioinformatics and statistical analysis methods to large scale genomic data analysis. In this vibrant inter-disciplinary research environment, there are opportunities for career growth, publish and write grants.

As a successful candidate, you will:

• Perform statistical and bioinformatics analyses of large scale genomic data, e.g. RNA-seq, single cell RNA-seq, WGS, whole exome-seq, etc.

• Prepare summaries, presentations, manuscript sections and figures for the visualization and publication of complex data and results.

• Evaluate existing methods and develop applications for genomic data analysis and data mining

• Enhance professional growth and development by reviewing current literature and by participation in educational programs, workshops, conferences, and meetings.

• Efficiently evaluate, prioritize and handle multiple and changing projects and priorities.

• Maintain department records, reports, and files as required.

• Attend a minimum of one in-person meeting on Duarte campus weekly, and ad hoc meetings hosted by TSLC laboratory faculty virtually or in-person, as required.



• Ph.D. in Bioinformatics, Molecular Biology, Genetics, Epigenetics, Biostatistics or Computer Science with experience in advanced single cell and spatial transcriptomics analysis

• 5+ years of relevant experience in applying statistical and computational methods to the analysis and visualization of complex genomics data.

• Experience with PacBio long reads analysis is a plus.

• Experience with genomic data integration and data mining, including but not limited to RNA-seq, WGS, WES, ChIP-seq, ATAC-seq, and spatial transcriptomics data

• Experience working with various NGS data, such as Illumina Hiseq/miSeq and PacBio SMRT sequencing

• Familiar with at least one programming languages, such as R/Perl/Python/JAVA/C++ with R or Python preferred

• Familiar with Biological databases, such as GEO and TCGA

• Familiar with open source and commercial software tools for genomic data analysis, such as BWA, STAR, Seurat, CellChat, IGV, VARSCAN, GATK, ANNOVAR, IPA, MAJIQ, Voila etc.

City of Hope is an equal opportunity employer. To learn more about our commitment to diversity, equity and inclusion, please click here