Bioinformatics Staff Scientist – Molecular Genetic Pathology, Hybrid

1.0 FTE Full time Day - 08 Hour R2657721 Hybrid 107520006 Path Lab Molecular Path Hillview Allied Health PALO ALTO, 3375 Hillview Ave, California
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Day - 08 Hour (United States of America)
The ideal applicant for this role would possess the following qualifications:
Expertise in cancer genomics and NGS technologies including somatic variant calling
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, etc
Experience using public annotation sources such as ClinGen, ClinVar, HGMD, cbGap, EVS, 1000 Genomes, gnomAD, and DGV
Licenses and Certifications
None .
These Principles Apply To ALL Employees
SHC Commitment to Providing an Exceptional Patient & Family Experience
Stanford Health Care sets a high standard for delivering value and an exceptional experience for our patients and families. Candidates for employment and existing employees must adopt and execute C-I-CARE standards for all of patients, families and towards each other. C-I-CARE is the foundation of Stanford’s patient-experience and represents a framework for patient-centered interactions. Simply put, we do what it takes to enable and empower patients and families to focus on health, healing and recovery.
You will do this by executing against our three experience pillars, from the patient and family’s perspective:
Know Me: Anticipate my needs and status to deliver effective care
Show Me the Way: Guide and prompt my actions to arrive at better outcomes and better health
Coordinate for Me: Own the complexity of my care through coordination
Equal Opportunity Employer Stanford Health Care (SHC) strongly values diversity and is committed to equal opportunity and non-discrimination in all of its policies and practices, including the area of employment. Accordingly, SHC does not discriminate against any person on the basis of race, color, sex, sexual orientation or gender identity and/or expression, religion, age, national or ethnic origin, political beliefs, marital status, medical condition, genetic information, veteran status, or disability, or the perception of any of the above. People of all genders, members of all racial and ethnic groups, people with disabilities, and veterans are encouraged to apply. Qualified applicants with criminal convictions will be considered after an individualized assessment of the conviction and the job requirements.
Base Pay Scale: Generally starting at $54.27 - $71.91 per hour
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, specialty and training. This pay scale is not a promise of a particular wage.