Staff Scientist – Pathology & Immunology Full-time

Staff Scientist In Computational Biology And Multi-Omics

We are seeking a highly motivated Staff Scientist in Computational Biology and Multi-Omics to develop, implement, and maintain computational pipelines for the analysis of high-dimensional genomic and spatial-omics datasets. The successful candidate will work closely with experimental scientists to analyze complex biological datasets, develop reproducible computational workflows, and integrate information across multiple molecular and cellular modalities.

Primary Duties & Responsibilities:

• Following instructions and discussions with the principal investigator, designs research protocols, including developing procedures for the collection, verification and management of data.
• Develop, implement, optimize, and maintain robust computational pipelines for single-cell and multi-omic data analysis, including scRNA-seq and spatial transcriptomic datasets.
• Establish and maintain workflows for 10x Genomics (preferably scRNAseq, Xenium, scATAC and multi-ome), smartseq datasets; related experience in image and transcript quality control, cell segmentation assessment, transcript assignment, cell-type annotation, spatial neighborhood analysis, and integration with complementary single-cell datasets.
• Perform end-to-end analysis of scRNA-seq datasets, including: raw data processing and quality control; normalization and dimensionality reduction; batch correction and data integration; clustering and cell-type annotation; differential gene-expression analysis; pathway and gene-set enrichment analysis; characterization of cellular heterogeneity and cell-state changes.
• Develop and run/conduct reproducible computational workflows using scripting and workflow-management tools and maintain well-documented analysis pipelines that can be reused across projects.
• Perform statistical analyses and develop publication-quality visualizations of complex multi-dimensional datasets.
• Work collaboratively with experimental biologists to formulate analytical strategies, interpret results in their biological context, and identify additional analyses or experiments needed to test emerging hypotheses.
• Provide guidance on experimental design for sequencing and spatial-omics studies, including considerations related to sample size, sequencing depth, batch effects, technical controls, and downstream analytical requirements.
• Establish procedures for computational quality control, data organization, metadata management, version control, and reproducibility.
• Manage analysis of large datasets using institutional high-performance computing environments and/or cloud-based computational resources.
• Troubleshoot computational workflows and identify technical or biological sources of unexpected results.
• Maintain awareness of new developments in single-cell genomics, spatial biology, computational biology, and multi-omic data integration and introduce useful new approaches into the laboratory's analytical framework.
• Contribute computational analyses, figures, and methodological descriptions to manuscripts, grant applications, presentations, and collaborative research projects.
• Maintain clear documentation of analytical methods, software versions, parameters, and computational workflows.
• Where appropriate, train and support laboratory members in computational analysis, data visualization, and best practices for reproducible research.

Working Conditions:

• Works in a laboratory environment with potential exposure to biological and chemical hazards.
• Must be physically able to wear protective equipment and to provide standard care to research animals.

The above statements are intended to describe the general nature and level of work performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all job duties performed by the personnel so classified. Management reserves the right to revise or amend duties at any time.