The Knott Laboratory at Cedars-Sinai Medical Center is seeking to hire a highly motivated computational scientist to fill the position of Research Bioinformatician II!

This position provides excellent opportunities for continued scientific development and contributions at the interface between research and clinical translation in dynamic laboratory environments. At the Knott laboratory, we utilize human samples and mouse models to generate multi-omic datasets using single-cell RNA- and ATAC-seq, ChIPseq, Proteomics, Spatial Transcriptomics and Functional Genomics. Our ultimate goal is to integrate these data to provide deeper knowledge of the interplay between the tumor and its immune microenvironment and how these interactions provide support for tumor evolution via plasticity, metastatic progression, and therapy resistance. The Research Bioinformatician II will be a critical team member that provides data that will inform follow-up functional validation experiments that provide meaningful rationale for the initiation of first in human clinical trials. To learn more, please visit: Knott Research Lab | Cedars-Sinai.

The Research Bioinformatician II (RBII) 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 will also work 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 RBII will demonstrate continuous self-improvement, make effective contributions to the section, and adhere to CSHS compliance plan, code of conduct, and hospital and departmental policies and procedures.

Primary Job Duties & Responsibilities:

• Provides general bioinformatics analysis support for omic projects and mainly responsible for data analysis and software compilations including next generation sequence alignment, polymorphism identification, expression analysis, and visualization tools and browsers.
• Summarizes data analyzes results in the form suitable as the basis for the first draft of written reports, and makes preliminary interpretations of the data.
• Develop, test, and maintain 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
• Transforms and merges multilevel omic data into user-friendly formats, assists in the development, tests, and maintains modular software pipelines, provides bioinformatics data analysis and preliminary interpretation of the data, and reports of the results for possible publications
• Familiar with medical and biological terminologies, bioinformatics resources, and national biological databases, Ready to provide solutions for investigator’s problems through data mining and extraction
• Identify, evaluate, and incorporate relevant algorithms and software pipelines by reviewing pertinent literatures in bioinformatics and computational biology
• Assists or collaborate in the preparation of grant proposals, publications, and presentations involving omic data
• Educate others about bioinformatics through mentoring of and teaching colleagues, investigators, fellows, and graduate students.

Department-Specific Responsibilities:

• Data analysis, integration, and interpretation of data.
• Management of data-sets.
• Interact with our bench collaborators to guide and propose new experiments.
• Participate and present research outputs in group meetings, collaborative meetings, project retreats and seminars.
• Assists with grant applications and annual grant reports.

Education:

• Master 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 a concentration in bioinformatics) is required.
• Doctorate is preferred.

Experience & Skills:

• Three (3) years in a research environment.
• Background and work knowledge in algorithms, scientific computing, and machine learning or statistics.
• Previous experience with C/C++, Java, Perl, python, and the Unix (Linux) environment.
• Experiences in manipulating, analyzing, and annotating very large genomic (e.g. NGS) data sets both in exploratory and pipelined fashions.