Stanford Blood Center
Senior Bioinformatician (2 Year Fixed Term)
Stanford Blood Center, Palo Alto, California, United States, 94306
Stanford Center for Genomics and Personalized Medicine (SCGPM), situated in the heart of SF Bay Area, has an excellent opportunity available for a motivated bioinformatician. This position within our bioinformatics core team will support bioinformatics consulting services for faculty and researchers via the Genetics Bioinformatics Service Center (GBSC). For examples of the projects we support, please visit
https://med.stanford.edu/gbsc/services/baas.html . The ideal person for this position is a bioinformatician who lives and breathes NGS data analysis and is passionate about learning. The successful candidate will have deep knowledge of NGS technologies, quality analysis for read alignment and variant calling (secondary analysis), and a large suite of analytical methods for discovering genetic components of human diseases (tertiary analysis). Responsibilities will include: Meeting faculty members and researchers to evaluate their bioinformatics needs. Conducting data analysis that meets quality standards of major peer-reviewed publications. Providing faculty members and researchers with data, analysis protocols, figures, method descriptions, code, documentation, support, and anything else that might be needed to meet project goals. Managing time and projects efficiently to support the analysis needs of multiple labs simultaneously. Establishing, refining, and standardizing the process for bioinformatics analysis and validation. Benchmark-driven development is expected, e.g., use of PrecisionFDA/Genome-¬in-¬a-¬Bottle for DNA¬Seq analysis, or the use of well-characterized data or simulated data where commonly-used reference datasets do not exist. Presenting bioinformatics efforts and best-practices at conferences and symposia. Peer-reviewed publications with and outside of client laboratories are strongly encouraged. Delivering quick proof-¬of¬-concept feedback on new methods and protocols. Providing training to researchers to allow them to learn and use new techniques for analysis. Staying abreast with bioinformatics best-practices (e.g., large consortium Data Coordination Centers like ENCODE and HMP) as well as cutting¬-edge data analysis methods from recent publications. Meeting 3rd party developers, service providers, and consortium members to stay on top of development of new tools, solutions, and practices in the field. Observing the highest standards of customer interaction, including maintaining confidentiality when required. The GBSC bioinformatics service team is supported by a group of expert software developers and biomedical engineers who are proficient in a variety of development environments, including large HPC clusters and multiple cloud platforms (e.g., DNAnexus, Google Cloud Platform). Members of this team are expected to participate in activities that are important to the center’s mission, including participation in conferences, arranging seminars, and attending annual retreats and other academic events as necessary. REQUIRED QUALIFICATIONS: PhD in Bioinformatics, Computational Biology, Physics, Computer Science or related field. Ability to define and solve logical problems for highly technical applications. Deep understanding of next¬-generation sequencing data and bioinformatics algorithms. While Illumina sequencers are the most common data source, it is not unusual to see 10xGenomics or PacBio data. Provide best-¬practices data analysis, including QC and visualization, employing common NGS pipelines such as RNA¬seq, ChIP¬-seq, ATAC-seq, Methyl-seq, DNA¬-seq, and Microbiome Sequencing. Multi¬omics analysis is often needed. Proven experience working in a Linux cluster environment. Experience in cloud environments is also a plus. Ability to select, adapt, and effectively use a variety of programming methods. Strong programming skills in Python and R are expected. Familiarity with C, C++, Java, and Perl are useful. Best practices in coding, including techniques of reproducible and transparent science (github, DockerHub, markdown documentation) will be required. Excellent verbal and written communication skills with both technical and non¬technical clients. Stanford offers a supporting learning environment and ability to learn rapidly is a critical need. Our service supports a large and growing customer base and Stanford researchers are engaged in innovative basic science research. We expect our team members to ramp up rapidly to support this innovation. Strong work ethics are critical in this role, since the individual will be responsible for the highest quality scientific data analysis. DESIRED QUALIFICATIONS: Postdoctoral training in one of the disciplines listed above is highly desirable for this position. While a wide background in NGS bioinformatics will be useful, deep experience with DNA¬-seq and/or RNA-seq data is strongly preferred, including whole genome, whole exome, SNP¬-array, tumor/¬normal. Strong background in one or more of the following: pedigree analysis, machine learning, statistical methods, variant annotation and interpretation, Genome Wide Association Studies (GWAS). Knowledge of general principles for regulatory compliance, including understanding of the NIH Security Best Practices for Controlled ¬Access Data Subject to the NIH Genomic Data Sharing (GDS) Policy (aka dbGaP compliance). The core team has developed an extensive set of data analysis pipelines on the local cluster and Cloud. We expect reuse of these pipelines. Candidate is also expected to add to this analysis library by developing custom/novel pipelines. Experience working in academic environments. Experience with mentorship or project management. Contact information: Please direct all applicants to
http://stanfordcareers.stanford.edu/
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University’s research, teaching and clinical missions. Compensation: The expected pay range for this position is $90,000 to $117,000 per annum. Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years since their applicable education, field or discipline; departmental budget availability; internal equity; among other factors. COVID-19 Policy: As an organization that receives federal funding, Stanford University has a COVID-19 vaccination requirement that will apply to all university employees, including those working remotely in the United States and applicable subcontractors. To learn more about COVID policies and guidelines for Stanford University Staff, please visit
https://cardinalatwork.stanford.edu/working-stanford/covid-19/interim-policies/covid-19-surveillance-testing-policy .
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https://med.stanford.edu/gbsc/services/baas.html . The ideal person for this position is a bioinformatician who lives and breathes NGS data analysis and is passionate about learning. The successful candidate will have deep knowledge of NGS technologies, quality analysis for read alignment and variant calling (secondary analysis), and a large suite of analytical methods for discovering genetic components of human diseases (tertiary analysis). Responsibilities will include: Meeting faculty members and researchers to evaluate their bioinformatics needs. Conducting data analysis that meets quality standards of major peer-reviewed publications. Providing faculty members and researchers with data, analysis protocols, figures, method descriptions, code, documentation, support, and anything else that might be needed to meet project goals. Managing time and projects efficiently to support the analysis needs of multiple labs simultaneously. Establishing, refining, and standardizing the process for bioinformatics analysis and validation. Benchmark-driven development is expected, e.g., use of PrecisionFDA/Genome-¬in-¬a-¬Bottle for DNA¬Seq analysis, or the use of well-characterized data or simulated data where commonly-used reference datasets do not exist. Presenting bioinformatics efforts and best-practices at conferences and symposia. Peer-reviewed publications with and outside of client laboratories are strongly encouraged. Delivering quick proof-¬of¬-concept feedback on new methods and protocols. Providing training to researchers to allow them to learn and use new techniques for analysis. Staying abreast with bioinformatics best-practices (e.g., large consortium Data Coordination Centers like ENCODE and HMP) as well as cutting¬-edge data analysis methods from recent publications. Meeting 3rd party developers, service providers, and consortium members to stay on top of development of new tools, solutions, and practices in the field. Observing the highest standards of customer interaction, including maintaining confidentiality when required. The GBSC bioinformatics service team is supported by a group of expert software developers and biomedical engineers who are proficient in a variety of development environments, including large HPC clusters and multiple cloud platforms (e.g., DNAnexus, Google Cloud Platform). Members of this team are expected to participate in activities that are important to the center’s mission, including participation in conferences, arranging seminars, and attending annual retreats and other academic events as necessary. REQUIRED QUALIFICATIONS: PhD in Bioinformatics, Computational Biology, Physics, Computer Science or related field. Ability to define and solve logical problems for highly technical applications. Deep understanding of next¬-generation sequencing data and bioinformatics algorithms. While Illumina sequencers are the most common data source, it is not unusual to see 10xGenomics or PacBio data. Provide best-¬practices data analysis, including QC and visualization, employing common NGS pipelines such as RNA¬seq, ChIP¬-seq, ATAC-seq, Methyl-seq, DNA¬-seq, and Microbiome Sequencing. Multi¬omics analysis is often needed. Proven experience working in a Linux cluster environment. Experience in cloud environments is also a plus. Ability to select, adapt, and effectively use a variety of programming methods. Strong programming skills in Python and R are expected. Familiarity with C, C++, Java, and Perl are useful. Best practices in coding, including techniques of reproducible and transparent science (github, DockerHub, markdown documentation) will be required. Excellent verbal and written communication skills with both technical and non¬technical clients. Stanford offers a supporting learning environment and ability to learn rapidly is a critical need. Our service supports a large and growing customer base and Stanford researchers are engaged in innovative basic science research. We expect our team members to ramp up rapidly to support this innovation. Strong work ethics are critical in this role, since the individual will be responsible for the highest quality scientific data analysis. DESIRED QUALIFICATIONS: Postdoctoral training in one of the disciplines listed above is highly desirable for this position. While a wide background in NGS bioinformatics will be useful, deep experience with DNA¬-seq and/or RNA-seq data is strongly preferred, including whole genome, whole exome, SNP¬-array, tumor/¬normal. Strong background in one or more of the following: pedigree analysis, machine learning, statistical methods, variant annotation and interpretation, Genome Wide Association Studies (GWAS). Knowledge of general principles for regulatory compliance, including understanding of the NIH Security Best Practices for Controlled ¬Access Data Subject to the NIH Genomic Data Sharing (GDS) Policy (aka dbGaP compliance). The core team has developed an extensive set of data analysis pipelines on the local cluster and Cloud. We expect reuse of these pipelines. Candidate is also expected to add to this analysis library by developing custom/novel pipelines. Experience working in academic environments. Experience with mentorship or project management. Contact information: Please direct all applicants to
http://stanfordcareers.stanford.edu/
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford welcomes applications from all who would bring additional dimensions to the University’s research, teaching and clinical missions. Compensation: The expected pay range for this position is $90,000 to $117,000 per annum. Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years since their applicable education, field or discipline; departmental budget availability; internal equity; among other factors. COVID-19 Policy: As an organization that receives federal funding, Stanford University has a COVID-19 vaccination requirement that will apply to all university employees, including those working remotely in the United States and applicable subcontractors. To learn more about COVID policies and guidelines for Stanford University Staff, please visit
https://cardinalatwork.stanford.edu/working-stanford/covid-19/interim-policies/covid-19-surveillance-testing-policy .
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