Research Assistant

SupportFinity™; New York (NY); On-site; USD 54,938 - 67,146; Full time

Job summary

A prominent research institution in New York is seeking a highly qualified Research Assistant to join their team. The successful candidate will have expertise in programming languages such as Python and R, with experience in data science and bioinformatics. This role will involve developing computational methods to analyze complex biological data, primarily focusing on RNAseq and spatial transcriptomics. The position offers a competitive salary and supports innovative research in neurodegenerative diseases.

Qualifications

• A Bachelor’s degree and at least one and one-half years of related experience or equivalent.
• Knowledge of related laboratory procedures and techniques required.
• Previous experience aligning Fastq files and expertise in spatial transcriptomics preferred.

Responsibilities

• Perform all analytical steps for RNAseq, single nucleus RNAseq, and spatial transcriptomics.
• Oversee progress of ongoing research projects, ensuring timely completion of milestones.
• Prepare scientific papers, progress reports, and presentations for conferences.

Skills

Data analysis

Expertise in Python

Expertise in R

Bioinformatics tools

Single-cell RNAseq analysis

Education

Bachelor's degree

Master's degree in bioinformatics

Tools

CellRanger

SpaceRanger

Seurat

Monocle

Job description

Job Information

• Technical Grade 5
• Job Type: Support Staff - Union
• Bargaining Unit: SSA
• Regular/Temporary: Regular
• Hours Per Week: 35
• Salary Range: $61,042.40 - $61,042.40

Position Summary

The Al-Dalahmah laboratory's mission is to define the states of glial pathology in neurologic diseases like neurodegeneration and glioblastoma. We use this knowledge to develop novel therapeutic strategies to block disease progression.

We are seeking a highly qualified Research Assistant with expertise in data science and bioinformatics to join our team. The ideal candidate will be an expert in programming languages such as C, Python, and R, with significant knowledge of single-cell RNAseq analysis. This role will focus on developing and applying computational methods to analyze complex biological data, contributing directly to the lab's research goals.

Responsibilities

• Data Analysis – 65%
  • Perform all analytical steps for RNAseq, single nucleus RNAseq, and spatial transcriptomics.
  • Develop and implement new computational methods for analyzing spatial transcriptomics and long-read sequencing data.
  • Conduct image analysis related to spatial transcriptomics experiments.
  • Adapt analytical approaches to integrate with wet-lab experiments and optimize data pipelines.
• Administrative – 10%
  • Oversee progress of ongoing research projects, ensuring timely completion of milestones.
  • Train and mentor junior personnel in coding, data analysis techniques, and best practices.
  • Coordinate with internal teams and collaborators to support project needs.
• Communication – 10%
  • Prepare scientific papers, progress reports, and presentations for conferences.
  • Communicate findings clearly to both computational and non-computational team members.
• Data Acquisition and Organization – 10%
  • Organize, manage, and maintain large-scale sequencing datasets for reproducible analyses.
  • Collaborate with wet-lab personnel on experimental design, data collection, and data annotation.
• Other duties as assigned – 5%

Minimum Qualifications

• A Bachelor’s degree and at least one and one-half years of related experience or equivalent in education, training and experience. Knowledge of various related laboratory procedures and techniques required.

Preferred Qualifications

• A Master's degree in bioinformatics is a plus. A background in mathematics and/or biology is preferred. Previous experience aligning Fastq files, performing single nucleus and spatial RNAseq analysis, and expertise in spatial transcriptomics and cancer biology are also preferred.
• Four years of related experience is recommended.

Other Requirements

• Expertise in Python and R. Proficiency with bioinformatics tools such as CellRanger, SpaceRanger, Seurat, and Monocle. Knowledge of deep learning, FACS, and image analysis.

Equal Opportunity Employer / Disability / Veteran

Columbia University is committed to the hiring of qualified local residents.