Organization Overview

Cancer remains a daunting problem despite decades of active research into its molecular causes. Such studies have predominantly focused on the earliest stages of cancer progression,such as the formation of a cancer or genes involved in the growth of the primary tumor. In humans afflicted by cancer,the primary tumor is typically surgically resected or eliminated by radiation. Vast numbers of patients,nonetheless,die of cancer as a result of metastasis or the spread of cancer cells from the primary tumor site to distal organs. This process is,in fact,the overwhelming cause of death from cancer,and its occurrence changes a patient's prognosis to incurable. Despite its vast clinical significance and inherently fascinating underlying biology,the metastatic program is poorly understood both at the molecular level and at the cellular/tissue micro-environment levels. Our laboratory employs a multi-disciplinary approach involving molecular,biochemical,computational,imaging,and clinical association methods to characterize the critical regulatory pathways that mediate the steps of this process. By implanting human cancer cells obtained from patients with breast or colon cancer into recipient mice,we study and interfere with the various stages of metastasis. By comparing human cancer cells that are highly metastatic to those that fail to metastasize,we have uncovered a set of small RNA molecules (microRNAs) that suppress metastasis. Our future work is aimed at gaining a better understanding of the mechanisms by which these microRNAs block metastasis. Our hope is that a better understanding of this process will enhance our therapeutic arsenal against it.

Overview

As a Bioinformatics Assistant II, you will be trained in the analysis and interpretation of next-generation sequencing (NGS) data, originating from mouse experiments of cancer metastasis as well as patients, under the guidance of postdoctoral scientists and bioinformaticians.

Responsibilities

Responsibilities include:

• Learn and assist in analyzing sequencing data using established pipelines

• Learn and perform appropriate QC measures

• Learn and develop/benchmark new tools for sequencing data analysis

• Assist and collaborate with internal and external researchers in interpretation of sequencing data

• Other responsibilities, as assigned

Qualifications

Requirements:

• Bachelor's degree is required; Master's degree or equivalent experience preferred

• Team-oriented

• Excellent written and verbal communication skills

• Collaboration skills and an eagerness to learn

• A working understanding of code and script

Preferred:

• Exposure to NGS data analysis preferred

• Training in statistics or machine learning is a plus.

The Rockefeller University does not discriminate in employment on the basis of race, color, religion, sex (including pregnancy, gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service or other non-merit factor. All qualified applicants will receive consideration for employment without regard to the characteristics listed above.

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

Compensation Range: Min

USD $55,000.00/Yr.

Compensation Range: Max

USD $65,000.00/Yr.