The Kalbasi Lab studies the interface between cancer and the immune system to gain new insights that will inform advances in cancer immunotherapy and radiation therapy.
Requirements
- Strong background in bioinformatics and biostatistics, including experience with analysis of next-generation sequencing data.
- Ideal candidates will also have experience with machine learning/AI tools, and experience with or interest in protein design.
- Experience and comfort in working within a UNIX/Linux environment.
- Background in programming languages such as Python, R, Matlab, Perl.
- Knowledge of techniques for analyzing tumor purity and clonal heterogeneity.
- Familiarity with predictive modeling and machine learning.
- Skills in machine learning and data analysis software.
Responsibilities
- Collect, manage and clean datasets.
- Employ new and existing tools to interpret, analyze, and visualize multivariate relationships in data, and for protein design.
- 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.
Other
- Bachelor's, MS, or PhD degree in Bioinformatics, Computation Biology or Computer Science or a related field with two years of relevant experience.
- Good communication and team skills and fluency in both spoken and written English.
- Ability to prioritize workload.
- Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
