Staff Associate I Full-time

Responsibilities include, but are not limited to the following:

• Under the direction of the PI, develop novel mutation clustering algorithms based on existing mathematical results from population genetics.
• Under the direction of the PI, evaluate new mutation clustering pipelines with synthetic tests.
• Under the direction of the PI, apply the pipelines to existing cancer DNA-sequencing datasets and derive biologically relevant findings.
• Present our findings to the community at national conferences.
• Participate in weekly meetings with the PI, his group and collaborators

Minimum Qualifications:

• A Master’s degree in mathematics, statistics, computer science, biology, or other related areas of science or engineering is required.
• Fluency in R and high-performance computing

Preferred Qualifications:

• The ideal candidate must possess strong organizational skills, keep excellent notes, show sound judgment, and have a collaborative style that fosters teamwork and cooperation as well as the ability to work independently within a diverse and dynamic team environment.
• Prior experience with DNA-sequencing data and processing pipelines is desirable but not required.
• Prior knowledge in population genetics and associated mathematical results is desirable but not required.

Tagged as: Computer Science, Life Sciences, Mathematics