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Desired Qualifications:
- MS in Computational Biology, Bioinformatics or other quantitative field plus 1-2 years experience; or equivalent
- Application of causal network modeling approaches such as Bayesian probabilistic graphical models
- Knowledge and experience with deep learning approaches
- Prior experience collaborating on multiple projects
- Experience contributing to writing grant proposals
- Knowledge and application of survival analysis in the context of high-dimensional data
- Hands-on experience using and applying spatial analysis methods for spatial transcriptomics (e.g. Visium) and proteomic (e.g. cycIF, CODEX, MIBI) analysis of cancer tissues
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.
- Expertise in biology-driven projects and a background of contributing to peer-reviewed publications
- Ability to work independently under overall guidance
- Experience analyzing and interpreting genomic and proteomic data such as CyTOF, CODEX, single cell RNA-seq.
- Familiarity with spatial transcriptomics and proteomics platforms and their use in cancer research
- Analysis of high-throughput sequencing such as whole genome/exome, RNA-sequencing
- Familiarity with machine learning/algorithms/computational methods
- Experience in Unix/Linux computing environment including high performance clusters
- Experience with relevant programming languages such as Python and R.
- Building web-based resources in R/Shiny
- Excellent oral and written communication skills
- Familiarity with molecular biology and/or cancer biology
- Strong interest in underlying science
Knowledge, Skills and Abilities (REQUIRED):
- Substantial experience with MS Office and analytical programs.
- Excellent writing and analytical skills.
- Ability to prioritize workload.
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.
- Due to the nature of the work, this position will be fully onsite.
The expected pay range for this position is $85,000 to $126,000 per annum. Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. 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 Stanfordʼs extensive range of benefits and rewards offered to employees. Specifics about the rewards package for this position may be discussed during the hiring process.
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.