Situated in Stanford’s highly dynamic research environment the Curtis Laboratory (http://med.stanford.edu/curtislab.html), led by Christina Curtis, PhD, is seeking a bioinformatician/Research Data Analyst 1 to join the Cancer Computational and Systems Biology group. The Curtis Laboratory is administratively situated within the Stanford Cancer Institute and is integrated within Stanford University and the School of Medicine’s Departments of Medicine (Oncology) and Genetics. The SCI is part of a Comprehensive National Cancer Institute Cancer Center for cross-disciplinary research in cancer biology involving researchers from oncology, radiobiology, computer science, genetics, statistics, and basic/translational clinical research. Our research couples state-of-the-art computational and experimental techniques to define novel therapeutic targets and biomarkers and to characterize tumor evolution.
The successful candidate will be part of an interdisciplinary research team developing novel technological and methodological approaches to improve the diagnosis, treatment and earlier detection of cancer. He/she will analyze and interpret large sequencing datasets by applying and developing bioinformatics and statistical methods for whole genome/exome sequencing, RNA-seq, ATAC-seq, single cell and spatial datasets. The successful candidate will interact closely with other computational and experimental biologists and clinicians to test, validate, and refine hypotheses. This is a fantastic opportunity for a motivated bioinformatician or computational genomicist to join a dynamic team with significant opportunities for scholarship.
Duties include:
- Collect, manage and clean datasets.
- Employ new and existing tools to interpret, analyze, and visualize multivariate relationships in data.
- Create databases and reports, develop algorithms and statistical models, and perform statistical analyses appropriate to data and reporting requirements.
- Use system reports and analyses to identify potentially problematic data, make corrections, and determine root cause for data problems from input errors or inadequate field edits, and suggest possible solutions.
- Develop reports, charts, graphs and tables for use by investigators and for publication and presentation.
- Analyze data processes in documentation.
- Collaborate with faculty and research staff on data collection and analysis methods.
- Provide documentation based on audit and reporting criteria to investigators and research staff.
- Communicate with government officials, grant agencies and industry representatives.
DESIRED QUALIFICATIONS:
- Bachelor’s degree (or higher) in Bioinformatics, Computer Science or a related field with one year (min) of relevant experience.
- Strong background in bioinformatics and biostatistics, including analysis of high-throughput sequencing data.
- Experience working within a UNIX/Linux environment.
- Fluency in programming languages such as Perl, Python, Java, R, C, Matlab; MySQL.
- Excellent communication and team skills and fluency in both spoken and written English.
- Familiarity with machine learning, information theory and signal processing.
- Experience with algorithm development.
- Familiarity with basic molecular biology.
- Background in cancer biology.
EDUCATION & EXPERIENCE (REQUIRED):
Bachelor's degree or a 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.
- Strong 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.
WORKING CONDITIONS:
Some work may be performed in a laboratory or field setting.
WORK STANDARDS:
- Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
- Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
- Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide.
