Are you ready to be a part of breakthrough research?

The Research Bioinformatician II performs general bioinformatics analysis and software support for projects involving in omics, and interacts with investigators to identify research problems, find appropriate software tools, and recognize national biological databases and online resources for omic data. The RBII manages omic data including loading and querying data from database system(s) and public repositories, and transforms and merges multilevel omic data into user-friendly formats. The RBII assists in development, testing, and maintenance of modular software pipelines, provides bioinformatics data analysis, preliminary interpretation of the data, and reports of the results for possible publications. The Research Bioinformatician II also works with bioinformatics faculties to determine future bioinformatics needs, and helps to develop tools and pipelines as necessary to keep pace with rapid advances in sequencing technology. The Bioinformatician II demonstrates continuous self-improvement, makes effective contributions to the section, and adheres to the Cedars-Sinai compliance plan, code of conduct, and hospital and departmental policies and procedures.

Primary Job Duties and Responsibilities:

• Provides general bioinformatics analysis support for omic projects. 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.
• Develops, tests, and maintains modular software pipelines for genome sequencing, assembly, annotation, metagenomic analysis, and genotyping using high-throughput sequencing platforms including 454, Illumina, and Pacific Biosciences.
• Manages data including loading and querying data from database systems, downloading omic data from public repositories, and transforming data to the necessary formats.
• Provides solutions for investigator?s problems through data mining and extraction.
• Identifies, evaluates, and incorporates relevant algorithms and software pipelines by reviewing pertinent literatures in bioinformatics and computational biology.
• Assists and/or collaborates in preparation of grant proposals, publications, and presentations involving omic data.
• Helps develop tools and pipelines as necessary to keep pace with rapid advances in sequencing technology.
• Educates others about bioinformatics through mentoring of and teaching colleagues, investigators, fellows, and graduate students.

Department-Specific Responsibilities:

• Process and analyze next-generation sequencing (NGS) data and genomic datasets.
• Use CLC Genomics Workbench for sequence alignment, variant calling, and subsequent data analysis.
• Develop and implement scalable data processing workflows on AWS (Amazon Web Services).
• Integrate and analyze data from public research databases such as GEO, ENA, TCGA, and dbGaP.
• Perform quality control (QC), preprocessing, and annotation of genomic data.
• Conduct statistical and computational analyses to interpret genomic variations and insights.
• Collaborate with biologists, clinicians, and data scientists to advance research objectives.
• Create detailed reports, visualizations, and documentation of analytical findings.
• Stay current with emerging tools and methodologies in genomic data analysis.

Education:

• Bachelor's of Science Degree in Computer Science, Electric Engineering, Computational biology, or Bioinformatics, or Master of Science/ Engineering in relevant fields (e.g. Biology with strong quantitative training, biostatistics with concentration in bioinformatics). Master's degree preferred.

Experience and Skills:

• Three (3) years of experience in research environment including developing working knowledge in algorithms, scientific computing, and machine learning or statistics.
• Three (3) years of experience in manipulating, analyzing, and annotating very large genomic (e.g. NGS) data sets both in exploratory and pipelined fashions.
• Familiar with C/C++, Java, Perl, python, and the Unix (Linux) environment.
• Proficiency in CLC Genomics Workbench for NGS data analysis.
• Experience with AWS cloud computing for large-scale genomic data processing.
• Strong coding skills in Python, R, or Bash for bioinformatics workflows.
• Familiarity with public genomic and research databases (GEO, ENA, TCGA, dbGaP, etc.).
• Expertise in NGS pipelines (e.g., RNA-Seq, WGS, WES, metagenomics).
• Knowledge of genetic variation analysis, population genetics, and annotation tools.
• Familiar with medical and biological terminologies, bioinformatics resources, and national biological databases.
• Previous experience with inflammatory bowel disease (IBD) research is highly desirable.