Bioinformatician/Research Data Analyst 1
Bioinformatician/Research Data Analyst 1🔍School of Medicine, Stanford, California, United States📁Information Analytics📅Apr 26, 2021 Post Date📅89303 Requisition #Situated in Stanford's highly dynamic research environment, the Moding and Binkley Laboratories (modinglab.stanford.edu), led by Everett Moding, MD, PhD and Michael Binkley, MD, MS are seeking a Bioinformatician/Research Data Analyst 1 to manage and analyze high throughput sequencing and clinical data from cancer patients under the direction of project researchers and investigators. The Laboratories perform translational cancer research by analyzing human tissue and blood samples with next-generation sequencing. Using a combination of state-of-the-art computational and experimental techniques, we aim to identify critical mediators of treatment resistance that can be validated in preclinical models and targeted to enhance the efficacy of cancer therapy. The laboratories are administratively situated within the Stanford University School of Medicine’s Department of Radiation Oncology. As an NCI-designated Comprehensive Cancer Center the Stanford Cancer Institute is a dynamic and stimulating place to work as it maintains the highest level of scientific rigor, institutional support, and coordination for the complete range of cancer-related research, including basic, translational, clinical and population-based science.
- 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.
- Develop machine learning and image processing software for research.
- Bachelor's, MS, or PhD degree in Bioinformatics, Computer Science or a related field with two years of relevant experience.
- Strong background in bioinformatics and biostatistics, including experience with analysis of next-generation sequencing data.
- Experience and comfort in working within a UNIX/Linux environment.
- Background in programming languages such as Python, R, Matlab, Perl.
- Good communication and team skills and fluency in both spoken and written English.
- Knowledge of techniques for analyzing tumor purity and clonal heterogeneity.
- A background in evolutionary biology and familiarity with phylogenetics techniques.
- Knowledge of Monte Carlo based statistical methods.
- Background in cancer biology.
- Familiarity with predictive modeling and machine learning.
- Bachelor's degree or a combination of education and relevant experience. Experience in a quantitative discipline such as economics, finance, statistics or engineering.
- Substantial experience with MS Office and analytical programs.
- Strong writing and analytical skills.
- Ability to prioritize workload.
- Skills in machine learning and data analysis software.
- Sitting in place at computer for long periods of time with extensive keyboarding/dexterity.
- Occasionally use a telephone.
- Rarely writing by hand.
- Some work may be performed in a laboratory or field setting.
- 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, http://adminguide.stanford.edu.
- Schedule: Full-time
- Job Code: 4751
- Employee Status: Regular
- Grade: G
- Department URL: http://radonc.stanford.edu/
- Requisition ID: 89303