Bioinformatician 2 – Computational Spatial Biology Full Time

Stanford University is seeking a Research Data Analyst 2 to manage and analyze large amounts of information, typically technical or scientific in nature, independently with minimal supervision.

Duties Include

• Prioritize and extract data from a variety of sources such as notes, survey results, medical reports, and laboratory data, and maintain its accuracy and completeness.
• Determine additional data collection and reporting requirements.
• Design and customize reports based upon data in the database. Oversee and monitor regulatory compliance for utilization of the data.
• Use system reports and analyses to identify potentially problematic data, make corrections, and eliminate root cause for data problems or justify solutions to be implemented by others.
• Create complex charts and databases, perform statistical analyses, and develop graphs and tables for publication and presentation.
• Serve as a resource for non-routine inquiries such as requests for statistics or surveys.
• Test prototype software and participate in approval and release process for new software.
• Provide documentation based on audit and reporting criteria to investigators and research staff.
• – Other duties may also be assigned

The expected pay range for this position is $108,002 to $128,138 per annum.

Stanford University provides pay ranges representing its good faith estimate of the salary or hourly wage the university reasonably expects to pay for a position upon hire. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location and external market pay for comparable jobs. At Stanford University, base pay represents only one aspect of the comprehensive rewards package.

The Cardinal at Work website (https://cardinalatwork.stanford.edu/benefits-rewards) provides detailed information on Stanford’s extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.

Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact Stanford University Human Resources at stanfordelr@stanford.edu. For all other inquiries, please submit a contact form.

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

Desired Qualifications

• MS or PhD in Computational Biology, Bioinformatics, Statistics, Computer Science, Biomedical Data Science, or a related quantitative field, with 1 to 2 years of relevant research experience.
• Experience analyzing and interpreting genomic, spatial omics, and proteomic datasets, including data generated from platforms such as Xenium, Visium, CosMx, CODEX, and single-cell RNA-seq, with demonstrated proficiency in single-cell RNA-seq analysis workflows.
• Prior experience analyzing the tumor microenvironment is highly desirable, along with familiarity with resources and databases related to cancer hallmarks, ligand–receptor interactions, and drug response.
• Strong interest in cancer biology and in deriving biologically meaningful insights from computational analyses; experience contributing to peer-reviewed publications is desirable.
• Proficiency in Python and R, including experience with commonly used analysis frameworks such as Seurat, scverse, and Bioconductor.
• Strong foundation in statistics, data analysis, and computational methods; familiarity with machine learning and algorithm development is desirable.
• Experience working in Unix/Linux computing environments, including use of high-performance computing clusters and, ideally, GPU-enabled workflows.
• Experience with GitHub, version control, and repository management for collaborative and reproducible research.
• Ability to work independently under general guidance, manage multiple priorities, and contribute effectively in a collaborative multidisciplinary research environment.
• Excellent oral and written communication skills, with a strong interest in connecting computational analysis to meaningful biological and translational questions.

Education & Experience (required)

Bachelor’s degree and three years of relevant experience or combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.

Knowledge, Skills And Abilities (required)

• Substantial experience with MS Office and analytical programs.
• Excellent writing and analytical skills.
• Ability to prioritize workload.

Certifications & Licenses

None

PHYSICAL REQUIREMENTS*:

• Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.
• Occasionally use a telephone.
• Rarely writing by hand.
• – Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of his or her job.

Working Conditions

Some work may be performed in a laboratory or field setting.

Additional Information

• Schedule: Full-time
• Job Code: 4752
• Employee Status: Regular
• Grade: I
• Requisition ID: 108863
• Work Arrangement : Hybrid Eligible