Genomics Bioinformatics Researcher I

Cedars-Sinai; Los Angeles (CA); On-site; USD 90,000 - 130,000; Full time

Job summary

Cedars-Sinai, through the Kao Autoimmunity Institute (KAI) on the West Coast, is seeking a Research Bioinformatician I to transform omics data into actionable insights. You will manage large genomic datasets, load from diverse sources, and help build modular software pipelines for sequencing projects.

The role involves daily data analysis, preliminary interpretation, and reporting for potential publications, with emphasis on collaboration across clinical and research teams at the Kao

Qualifications

• Bachelor's degree in a quantitative field is required.
• Experience in a research environment is highly preferred.
• Proficiency with programming languages and Unix/Linux is expected.

Responsibilities

• Perform bioinformatics analysis and support software for omics projects.
• Manage omic data, load/query from databases and public repositories.
• Develop and maintain modular pipelines for genome sequencing.
• Provide daily data analysis, preliminary interpretation, and reports.
• Review literature to identify relevant algorithms and tools.

Skills

C/C++

Java

Perl

Python

Unix/Linux

Algorithms

Machine learning

Statistics

Research experience

Education

Bachelor's Degree in CS/EE/Computational Biology/Bioinformatics

Job description

Job Description

Data is vital to advance clinical knowledge across a spectrum of medical and surgical fields. Are you ready to transform data discoveries into valuable information, which will empower tomorrow's medicine? We invite you to consider and apply to this great opportunity today!

About the Team

The Kao Autoimmunity Institute (KAI) is the first institute of its kind on the West Coast and was founded in 2019 through a generous donation from the Kao Family Foundation. The Institute's mission is to advance the knowledge and treatment of autoimmune diseases through research driven by excellent patient care. The KAI's team strives to educate the next generation of autoimmunity‑focused clinical and translational investigators. To learn more, please visit the Kao Autoimmunity Institute (KAI) website.

About the Role

The Research Bioinformatician I will perform general bioinformatics analysis and software support for projects involving in omics. The RB I member will manage omic data including loading and querying data from database systems and public repositories, and transforms and merges multilevel omic data into user-friendly formats. The incumbent assists in development, testing, and maintenance of modular software pipelines for genome sequencing, provides daily bioinformatics data analysis, preliminary interpretation of the data, and reports of the results for possible publications.

Primary Job Duties and Responsibilities:

• Responsible for data analysis and software compilations including next generation sequence alignment, polymorphism identification, expression analysis, and visualization tools and browsers.
• Summarizes data analyses results in the form suitable as the basis for the first draft of written reports, and makes preliminary interpretations of the data.
• Assists with assembly, annotation, metagenomic analysis, and genotyping using high-throughput sequencing platforms including 454, Illumina, and Pacific Biosciences.
• Manages and redefines data to the necessary formats.
• Helps to identify, evaluate, and incorporate relevant algorithms and software pipelines by reviewing pertinent literatures in bioinformatics and computational biology.

Qualifications

Education:

• Bachelor’s Degree in Computer Science, Electrical Engineering, Computational Biology, Bioinformatics, or relevant fields (e.g., Biology with strong quantitative training, Biostatistics with concentration in Bioinformatics) is required.

Experience:

• Experience in a research environment is highly preferred.
• Background and work knowledge in algorithms, scientific computing, and machine learning or statistics is preferred.
• Proficiency with C/C++, Java, Perl, python, and the Unix (Linux) environment.
• Experience in manipulating, analyzing, and annotating very large genomic (e.g. NGS) data sets, both in exploratory and pipelined fashions is highly preferred.