Stanford University is seeking a Computational Biologist/Research Data Analyst 2 to apply sophisticated computational methods to genomic and proteomic datasets in human disease.
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 to develop 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 as 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 start date is flexible.
About the Position:
The successful candidate will be part of a team developing and applying new 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 and single cell RNAseq, exome/genome sequencing data; as well as new high content imaging platforms such as CODEX, MIBI, CosMX, and Visium spatial transcriptomics. This opening for a computational biologist offers opportunities for 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). We also have ongoing projects in other areas such as neurodegenerative disease.
Uploading a CV/resume is highly recommended.
Duties include:
Analyzing genomic and other molecular datasets in relation to patient outcomes and treatment responses
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, 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 $100,000 to $113,000 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.
Why work at Stanford?Stanford University has changed the world, over and over again.We are one of Silicon Valley's largest employers - and also one of the most unique. Our mission is to educate future leaders and promote interdisciplinary, world-class research and teaching. This passion makes Stanford an intensely creative, rewarding, and challenging place to work. At the same time, our traditions of respect and collaboration sustain a humane, supportive environment in which to pursue your life and your career.At Stanford you'll work with bright, diverse, dedicated people. You'll find encouragement to learn and grow. You'll enjoy excellent benefits and an outstanding environment. How will it change you?
