Staff Associate I

The Department of Biological Sciences invites applications for a position of Staff Associate I (SAI) to begin June 1, 2026. The SAI will collaborate with interdisciplinary teams to develop advanced machine learning and computational biology models, build and maintain reproducible data analysis workflows, and analyze high-dimensional multimodal biological data (including imaging, spatial omics, and mass spectrometry) to generate insights into complex biological systems, while clearly communicating research findings. Under the supervision of the PI, the SAI’s responsibilities include:

• Collaborate with interdisciplinary team to develop and apply advanced machine learning and computational biology models to gain insight of complex biological processes
• Develop and implement computational workflow for image integration, cell segmentation, automated cell detection, cell-cell interactions and downstream data analytics
• Process, analyze and interpret high dimensional multimodal data from mass spectrometry imaging, spatial transcriptomics and spatial proteomics
• Develop integrative data analytics workflow for untargeted mass spectrometry data
• Maintain documentation of data analysis pipelines, processes and data models to ensure data integrity and reproducibility
• Communicate research findings through presentations, reports and contributions to peer-reviewed journals

Specific Duties

Technical Expertise 60%

Problem Solving Skills 10%

Decision Making/Autonomy 10%

Functional Knowledge 10%

Communication Skills 10%

Bachelors degree in Bioinformatics, Computer Science, Biostatistics, Data Science or a related field required.

Masters degree in Bioinformatics, Computer Science, Biostatistics, Data Science or a related field preferred.

Minimum of 2 years required, 4 years experience preferred

Specific skills and/or knowledge

• Proficient in Python and R to implement the relevant packages for single cell, bulk and spatial transcriptomics, metabolomics and targeted proteomics analysis
• Demonstrated ability to design and implement reproducible workflows for large scale data analysis
• Strong verbal and written communication skills

All applications must be made through Columbia University’s online recruiting system ASR; on the site, please upload cover letter, CV, and a list of 2 reference providers (who may be asked to provide a letter at a later date).

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.