Staff Associate I

The Staff Associate will assist with the application of computational methodologies to identify and pharmacologically target Master Regulators of molecularly distinct, yet co-existing cellular states in a complex set of human malignancies.He/she will interact and work with a team of computational and experimental scientists, providing assistance to the alignment, analysis and interpretation of data generated, including poster and oral presentations.

Functional Knowledge

• Use methodologies and algorithms developed by the lab to analyze scRNA-Seq sequencing data
• Assist with application of computational tools to identify Master Regulators that may
• Be targeted by existing FDA-approved drugs or late stage experimental compounds, using scRNA-Seq data generated in the lab
• Help students and postdocs to generate figures for grant submission and manuscript preparation
• Use of lab-specific computational tools and pipelines for scRNA-Seq analysis
• Data analysis and applied machine learning tools using programming languages such as Python, R, Java, C , JavaScript, MATLAB, SQL
• Basic knowledge of Bioinformatics and Cancer Biology

Problem Solving

• Advanced computational problem-solving abilities, proactive, task-oriented
• Ability to understand research questions and apply proposed solutions, including application of quantitative frameworks to generate quantitative solutions

Decision Making/Autonomy

• Level of supervision required, on a scale of 1 (least) to 10 (most) - # 3
• Degree of independent judgment expected, on a scale of 1 (least) to 10 (most) - # 7

Technical Expertise

• Computer languages and environments: Python, R, Java, C , JavaScript, MATLAB, SQL
• Knowledge of commonly used computational pipelines developed for scRNA-Seq data analysis

Communication

• Excellent communication of science-related topics, including Computer & Data Science, Biomedicine and Engineering

Minimum Qualifications

• Bachelor's degree in Computer & Data Science or related field
• 0-2 years of experience in data science, computational biology and/or bioinformatics

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.