Senior Scientist – Spatial Oncology Analytics

Stellaromics Inc.; Boston (MA); On-site; USD 120,000 - 170,000; Full time

Job summary

Stellaromics Inc. in Boston (with a San Diego option) seeks a hands-on Computational Oncology expert to lead our spatial biology initiatives, bridging raw molecular data with high-resolution biological insight.

Lead analyses of tumor microenvironment datasets, including cellular composition, spatial organization, and neighborhood dynamics; translate results into testable oncology hypotheses and adapt workflows.

Qualifications

• PhD in cancer biology, molecular biology, genomics, computational biology, or related field (or MS with equivalent industry experience).
• Fluent in spatial and single-cell computational concepts: segmentation, deconvolution, neighborhood analysis.
• Hands-on experience with major spatial platforms (Xenium, CosMx, GeoMx, MERSCOPE, Visium).

Responsibilities

• Lead computational analysis and interpretation of high-dimensional spatial and single-cell oncology datasets.
• Analyze tumor microenvironment biology including cellular composition, cell states, spatial organization, and tumor heterogeneity.
• Develop analytical approaches for segmentation, deconvolution, spatial neighborhood analysis, biomarker discovery, and tissue architecture characterization.
• Translate complex datasets into biologically meaningful hypotheses and actionable insights for oncology research.

Skills

Spatial biology

Single-cell analysis

Tumor microenvironment

Data integration

Computational biology

Communication

Education

PhD in cancer biology/genomics/computational biology

Tools

Xenium

CosMx

GeoMx

MERSCOPE

Visium

Job description

Stellaromics Inc. in Boston (with a San Diego option) seeks a hands-on Computational Oncology expert to lead our spatial biology initiatives, bridging raw molecular data with high-resolution biological insight.

Lead analyses of tumor microenvironment datasets, including cellular composition, spatial organization, and neighborhood dynamics; translate results into testable oncology hypotheses and adapt workflows.