Columbia University
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.
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.