Staff Associate I

Columbia University's Irving Institute for Cancer Dynamics unites world-class scientists across diverse academic disciplines to conduct groundbreaking research that transforms our understanding of cancer. Our mission is to combine expertise in mathematics, statistics, computer science, immunology and biology, to uncover how tumors evolve.

The laboratory of Dr. Khanh N. Dinh has an opening for a highly motivated Staff Associate I position to gain proficiency in a dynamic and collaborative research environment, assisting in developing novel bioinformatic software grounded in mathematics and biology to analyze tumor genomic data.

Responsibilities:

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.

Columbia University is an Equal Opportunity Employer / Disability / Veteran

Pay Transparency Disclosure

The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, and training. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.