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Day - 08 Hour (United States of America)
The ideal applicant for this role would possess the following qualifications:
o Expertise in cancer genomics and NGS technologies including somatic variant calling
o Familiarity with standard genomics/bioinformatics tools (e.g. Samtools, BWA, IGV)
This is a Stanford Health Care job.
A Brief Overview
The Bioinformatic Staff Scientist will be responsible for developing and maintaining Next Generation Sequencing data analysis workflows for use in a molecular genetic testing setting. This includes algorithms development as well as pipeline design. They will participate in development and implementation of bioinformatics tools for test development and validation, joining a team that develops leading-edge genomic assays and analysis tools that directly impact patient care.
Locations
Stanford Health Care
What you will do Develop, document and deploy novel clinical sequencing analysis approaches meeting CLIA and CAP guidelines for clinical NGS analysis
Develop, document and deploy in-house web-applications and databases for clinical genomics data storage, analysis and visualization
Enhance, maintain, and support established sequencing pipelines and workflows meeting CLIA and CAP guidelines for clinical NGS analysis
Develop, implement and maintain tools and workflows for system administration and data management
Collaborate with technical and medical teams in specifying requirements for tools to enhance workflow efficiency, turnaround times and robustness
Summarize results in written or oral reports for computational biologists, molecular biologists, clinicians, and internal researchers
Contribute to publishing of relevant findings in scientific journals
Education Qualifications Graduate Degree (Ph.D./M.S,) in bioinformatics, genetics and genomics, computer science or other work-related field/discipline from an accredited college or university
Experience Qualifications Ph.D. with no experience, or M.S. plus 3 years of experience developing pipelines and algorithms for computational biology, genomics, and/or clinical diagnostics preferred
Required Knowledge, Skills and Abilities Knowledge of algorithmic techniques common to bioinformatics (e.g., dynamic programming and graph algorithms), machine learning and statistical analysis methods (e.g., Bayesian inference, Hidden Markov Models, Principal Component Analysis)
Proficient in Python, competent in C++, Java, SQL, and R
Demonstrated experience in software development for bioinformatics applications
Experience with SQL and relational database design
Comfortable with Bash scripting and working in UNIX/Linux environments
Ability to produce readable, maintainable and well documented code
Experience with version control and source code management systems (e.g. Git)
Detail oriented mindset for working on applications that directly impact patient care
Ability to collaborate and communicate with other bioinformaticians, researchers and medical staff
Excellent problem-solving skills for common problems in bioinformatics
Familiarity with system administration and IT operations
Strong team-oriented work ethic with open, honest, and considerate communication skills
Preferred Knowledge, Skills and Abilities Molecular Pathology:
• Expertise in cancer genomics and NGS technologies including somatic variant calling
• Familiarity with standard genomics/bioinformatics tools (e.g. Samtools, BWA, IGV)
• Good understanding of human molecular genetics
• Experience analyzing genomic sequencing data from Illumina platforms
• Experience developing web-applications with Python and Django
Clinical Genomics:
• Familiarity with NGS data and best practices for germline sequencing
• Expertise in bioinformatics resources and tools such as BLAST, BWA, GATK, dbGaP, NCBI, EBI, UCSC genome browser,…