Sr. / Staff Scientist, Computational Biology

Cellanome•San Diego, CA

1d•$150,000 - $200,000

About The Position

We’re a well-funded start-up. You’ll get a chance to wear many hats, be a part of a growing team, and have the potential for exciting financial and career growth. Here’s what sets us apart. We’ve set our sights on some of the biggest challenges facing biology today. We’re amassing a world class team of engineers, scientists, team builders and problem solvers to tackle these challenges heads-on. We’re passionate about developing the next generation technologies that will unravel the complexities of biology. This is a unique opportunity to build, be part of an exciting start-up and be surrounded by good humans who are super capable, humble and down-to- earth. Cellanome is adding a Sr. or Staff Scientist, Computational Biology to the team (exact level dependent on experience). This role will lead computational analysis efforts in close collaboration with the core R&D teams and external collaborators, driving the analysis and interpretation of complex, multimodal biological datasets generated by the Cellanome platform.

Requirements

PhD in quantitative field (bioinformatics, biology, computational/systems biology, physics, mathematics). Typically requires at least 5 years of relevant experience.
Demonstrated expertise in single-cell sequencing analysis, supported by a strong scientific understanding of single-cell biology.
Strong background in molecular biology, cellular biology, genetics and/or biochemistry, with a solid understanding of biological principles and experimental techniques.
Proficiency in R and Python, with expertise in data visualization libraries (e.g., ggplot2, seaborn, matplotlib) to generate clear, insightful visualizations for both technical and non-technical audiences.
Proficiency with version control systems (e.g. Git/GitHub) and commitment to reproducible, well-documented workflows.
Excellent communication skills and ability to work independently and collaboratively in a multidisciplinary team environment.
Demonstrated ability to perform the Essential Duties of the position with or without reasonable accommodations

Nice To Haves

Track record of scientific contributions demonstrated through publications, preprints, or conference presentations.
Experience developing production-grade R/Python analysis packages with a focus on usability, scalability, and maintainability, including contributing to tools with a growing user base.
Familiarity with foundation models applied to biological data, such as single-cell transcriptomic models (e.g., scGPT, Geneformer) or self-supervised vision models for cellular morphology (e.g., DINO, MAE).
Experience developing interactive applications (e.g. Shiny, Streamlit) to streamline data exploration and reporting for diverse audiences, including collaborators and stakeholders.
Experience with cloud computing, preferably AWS.
Experience with analysis of imaging data, including fluorescence microscopy and/or flow cytometry.

Responsibilities

Partner with interdisciplinary scientists to shape experiment design, data collection strategies, analysis approaches, and interpretation of results.
Apply machine learning, statistical modeling, and emerging approaches such as foundation models to extract meaningful insights from large-scale biological datasets.
Lead end-to-end analysis of multimodal datasets, synthesize findings, and report results effectively to internal teams, leadership, and external stakeholders.
Translate findings into strategic recommendations that shape platform development priorities and analysis workflows.
Support the development and optimization of analytical pipelines and interactive tools for processing multimodal datasets generated by the platform.
Work at a computer for approximately 90% of a typical workday.