Stanford University is seeking a Research Data Analyst 1 (2 Year Fixed Term) to manage and analyze large amounts of information, typically technical or scientific in nature, under the direction of project researchers, investigators, or managers.

Overall responsibility

Collaborate on short- and long-term independent scientific projects to support the research objectives of the lab. Utilize engineering and programming skills to design and develop mathematical models for RNA folding and computational tools for predicting and visualizing RNA structure, protein binding and function. Analyze experimental data, address methodological problems in experimental protocols and results. Prioritize and organize workflow and in optimize experimental design structure, methodologies and analysis of results.

Research background and goals

RNA is unique among all biomolecules as it can be both information-storing and enzymatic. These features are tightly linked to its structure, in which base-pairing interactions give rise to a highly folded macromolecule. Indeed, in addition to the genetic code, which specifies the composition of proteins, we now know there is a secondary layer of information encoded in every transcript in the form of RNA structure that can regulate processes as diverse as splicing, localization, and translation efficiency. Recent genome-wide association and biochemical studies have linked multiple diseases, including cancer and neurodegenerative diseases, to changes in RNA structure and RNA binding proteins and their interactions. The project is first focused on developing new methodologies and mathematical models for RNA folding to answer fundamental and unresolved questions on the RNA-based regulation in gene expression and disease. From there it expands to RNA-protein interactions and downstream functional consequences.

Characteristic duties

• Develop and apply algorithms for analysis of large-scale biological data related to RNA folding and interactions
• Design systematic experimental libraries that can provide the needed experimental data
• Develop mathematical models for RNA structure incorporating empirical data
• Hypothesis testing using statistical concepts
• Utilize algorithms such as classification, regression and clustering to answer diverse research questions
• Work closely with collaborators and lab members on high-throughput sequencing analysis
• Enable collaborators and team members to run scripts effectively
• Perform ad hoc data analysis and data modeling tasks
• Exploratory projects related to RNA structure modeling

• - Other duties may also be assigned.