Bioinformatics Associate III

South San Francisco, CA 94080

Posted: 02/15/2019 Employment Type: Contract Industry: Research - Discovery Job Number: 5598

Duties:
  • The Department of Bioinformatics and Computational Biology at Genentech is seeking a highly motivated full-time computational biologist contractor to work with our team. The primary focus of this contractor position will be on the analysis and interpretation of high-throughput genomic and clinical data, to further our understanding of the biological processes involved in cancer initiation, maintenance, metastasis and resistance to therapy (a basic understanding of cancer biology is a plus for this position, but is not a requirement).

 

A successful computational biologist contractor will be expected to:

 

Analyze and interpret high-throughput molecular data (RNA-Seq, single-cell transcriptomics, etc) in the context of biological problems, in close collaboration with an interdisciplinary team of bench and computational scientists.

Integrate high-throughput molecular data with clinical outcome data to inform research programs Contribute to publications in high-quality scientific, technical, and medical journals (and receive publication credit for these contributions) Develop and maintain software of in-house computational tools

 

Skills: (required):
  • Familiarity with Linux working environment and high-performance computing recommended High level of proficiency with R programming language required (other scripting languages e.g. Python, perl, a plus) Experience in the analysis, visualization, and interpretation of high-throughput data Outstanding skills in problem-solving, communication, and collaboration with bench scientists and/or clinical scientists

 

Skills (desired):

Experience in standard bioinformatics toolkits and programs highly desired Experience with one or more high-throughput biological assays such as RNA-seq, single-cell RNA-seq, ATAC-seq, exome-seq and ChIP-seq is a plus, but not required

 

Education:
  • Masters or Ph.D. in a relevant field (such as computational biology, systems biology, bioinformatics, genomics, statistics, computer science, cancer biology, etc.)

Duties:

  • The Department of Bioinformatics and Computational Biology at Genentech is seeking a highly motivated full-time computational biologist contractor to work with our team. The primary focus of this contractor position will be on the analysis and interpretation of high-throughput genomic and clinical data, to further our understanding of the biological processes involved in cancer initiation, maintenance, metastasis and resistance to therapy (a basic understanding of cancer biology is a plus for this position, but is not a requirement).

 

A successful computational biologist contractor will be expected to:

 

Analyze and interpret high-throughput molecular data (RNA-Seq, single-cell transcriptomics, etc) in the context of biological problems, in close collaboration with an interdisciplinary team of bench and computational scientists.

Integrate high-throughput molecular data with clinical outcome data to inform research programs Contribute to publications in high-quality scientific, technical, and medical journals (and receive publication credit for these contributions) Develop and maintain software of in-house computational tools

 

Skills: (required):

  • Familiarity with Linux working environment and high-performance computing recommended High level of proficiency with R programming language required (other scripting languages e.g. Python, perl, a plus) Experience in the analysis, visualization, and interpretation of high-throughput data Outstanding skills in problem-solving, communication, and collaboration with bench scientists and/or clinical scientists

 

Skills (desired):

Experience in standard bioinformatics toolkits and programs highly desired Experience with one or more high-throughput biological assays such as RNA-seq, single-cell RNA-seq, ATAC-seq, exome-seq and ChIP-seq is a plus, but not required

 

Education:

  • Masters or Ph.D. in a relevant field (such as computational biology, systems biology, bioinformatics, genomics, statistics, computer science, cancer biology, etc.)
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