Stanford University is seeking a Computational Biologist/Research Data Analyst 2 to apply sophisticated computational methods to genomic and proteomic datasets in human cancer.
About the Department of Pathology
Comprised of extraordinary faculty and staff, our mission is to improve the ability to diagnose, treat, and understand the origin and manifestation of human disease and to care for those who have or are at risk of developing disease. We accomplish this through our clinical services and research which includes basic, translational and clinical research into the origins and manifestations of disease, including efforts to improve disease prediction and prevention as part of the goal of achieving precision medicine and health.
School of Medicine employees who are patient-facing, work in, or frequent clinical and hospital areas for work purposes are considered healthcare workers. This position is considered a healthcare worker and will need to comply with the Stanford Health Care COVID-19 vaccination requirements.
About the Lab:
Based within the Department of Pathology at Stanford University, the Gentles lab is seeking a Computational Biologist/Research Data Analyst 2 to join the group and contribute to projects related to human disease. We are using advanced computational and experimental techniques to identify biomarkers for cancer therapy, as well as to study basic questions in cancer biology related to identifying novel avenues for therapy, particularly immunotherapies. We view computational methods as tools for understanding biology and disease, and are motivated by the scientific questions that arise in complex systems. We are part of the NCI’s Cancer Systems Biology Consortium, as well as related efforts at Stanford around interdisciplinary approaches to biological and clinical questions. This position is available immediately, though the start date is flexible.
About the Position:
The successful candidate will be part of a team developing and applying modern methods and resources for cancer diagnosis and prognosis, as well as analyzing underlying mechanisms driving cancer behavior and patient outcomes. They will analyze complex genomic and proteomic datasets from patient cohorts, including bulk RNAseq, exome/genome sequencing data; as well as blood-based assays (e.g. circulating DNA and RNA). There may also be opportunity to analyze new high content imaging platforms such as CODEX, MIBI, CosMX, and Visium spatial transcriptomics. This opening for a computational biologist offers opportunities for a career contributing to exciting projects at the forefront of applying new molecular technologies to human disease. Our recent work includes developing resources and tools such as PRECOG and EcoTyper (Luca/Steen et al, Cell 2021).
Duties Include:
Analyzing genomic and other molecular datasets in relation to patient outcomes and treatment responses
Applying sophisticated machine learning approaches to such data and overall aims
Obtaining and pre-processing data from external resources such as public repositories
Assisting in the design and implementation of analysis plans to address scientific objectives
Collaborate with others in developing and implementing research projects
Preparing figures for publication, and helping to write manuscripts
Assist with documenting code and preparing annual grant progress reports
Interacting closely with other computational scientists as well as wet lab researchers and clinicians
Attend seminars, lectures, etc, to learn about new approaches and keep abreast of relevant cancer biology, genomics, and computational developments
Presenting results internally and to collaborators and other groups
* - Other duties may also be assigned
Desired Qualifications:
MS in Computational Biology, or other quantitative field plus 1-2 years experience or equivalent
Application of causal network modeling approaches such as Bayesian probabilistic graphical models or deep learning
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
Experience with processing and analyzing data from blood-based assays such as circulating tumor DNA
Building web-based resources in R/Shiny
Expertise in biology-driven projects and a background in contributing to peer-reviewed publications
Ability to work independently under overall guidance and prioritize projects as needed
Prior experience working on cancer-related datasets, particularly in relation to immunotherapy response
Familiarity with analysis of longitudinal (time series) data in relation to outcomes
Experience analyzing and interpreting genomic and proteomic data such as CyTOF, CODEX, and single-cell RNA-seq
Familiarity with machine learning/algorithms/computational methods such as sparse methods for regression such as lasso, elastic net, random forests; logistical and Cox regression; longitudinal (time series) data
Experience in Unix/Linux computing environments including high performance clusters and cloud compute (e.g. AWS) and relevant programming languages such as Python and R
Excellent oral and written communication skills with a strong interest in underlying science, not just in running pipelines
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.
Physical Requirements*:
Sitting in place at a 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 $104,358 to $128,038 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 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.
Why Stanford is for You
Imagine a world without search engines or social platforms. Consider lives saved through first-ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enrich the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy. Our culture and unique perks empower you with:
Freedom to grow. We offer career development programs, tuition reimbursement, or course auditing. Join a TedTalk, film screening, or listen to a renowned author or global leader speak.
A caring culture. We provide superb retirement plans, generous time-off, and family care resources.
A healthier you. Climb our rock wall or choose from hundreds of health or fitness classes at our world-class exercise facilities. We also provide excellent health care benefits.
Discovery and fun. Stroll through historic sculptures, trails, and museums.
Enviable resources. Enjoy free commuter programs, ridesharing incentives, discounts and more
The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.
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.
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.
School of Medicine, Stanford, California, United States
📁 Information Analytics
Post Date:Feb 21, 2025
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