Computational Biologist
Trailhead Biosystems
Software Engineering
Beachwood, OH, USA
USD 100k-120k / year
Computational Biologist
Información del empleo
Sueldo
- $100,000 - $120,000 por año
Tipo de empleo
- Full-time
Descripción completa del empleo
About Us
Trailhead Biosystems merges developmental biology with computerized experimental design to develop novel induced pluripotent stem cell (iPSC) research products. Trailhead Biosystems is the pioneer of High-Dimensional Design-of-Experiment (HD-DoE®), a powerful platform that differentiates human iPSCs into virtually any desired cell type with unparalleled precision and efficiency. We are moving beyond traditional trial-and-error methods by implementing Quality by Design principles and utilizing DoE combined with multivariate data analysis.
The Role
We are seeking a Computational Biologist to join our team to support product development and cellular engineering. Reporting to the Director of Bioinformatics and AI Engineering, the position will lead biological analytics at the company, and should have a deep understanding of statistical analyses including DoE, as well as genomic analyses including bulk or single cell RNA-sequencing. The position will collaborate with a team of iPSC Scientists, Database Engineers, and AI Engineers to achieve cutting edge life sciences innovation.
Responsibilities
- Design and build end-to-end bioinformatics pipelines from raw data ingestion through QC, analysis, and reporting, with a primary emphasis on bulk and single-cell RNA-sequencing workflows
- Build reproducible, scalable RNA-seq data processing pipelines including single-cell RNA-seq across multiple platforms. Provide guidance in library preparation strategies, including droplet-based, combinatorial indexing, and cell hashing approaches
- Extend pipeline capabilities to additional human omics modalities (e.g., ATAC-seq, proteomics, spatial transcriptomics) as project needs evolve
- Develop or use appropriate tools and algorithms for normalization, classification, dimensionality reduction, and clustering of high-dimensional omics datasets
- Build interactive visualization tools and applications for exploratory data analysis which enable Scientists to interrogate results without requiring direct bioinformatics support
- Generate analysis reports and summaries that translate computational findings into actionable biological insights
- Apply multivariate statistical methods to experimental datasets; support HD-DoE design, data acquisition, and downstream analytics in collaboration with R&D teams
- Create testing methods and perform quality checks on modules and algorithms prior to deployment; maintain SOPs for pipeline and analysis workflows
- Work with the database development team to architect data storage solutions, integrate analytics outputs, and establish data quality control policies
- Evaluate and provide input on third-party software tools; perform cost-benefit analyses for new analytics capabilities
- Stay current on developments in bioinformatics, data science, and AI; proactively identify opportunities to apply emerging methods
Skills and Qualifications
- PhD in Bioinformatics, Computational Biology, or a closely related quantitative field (Statistics, Computer Science, or similar with strong biological application)
- Deep expertise in RNA-sequencing analysis — bulk and single-cell — including pipeline construction, QC, normalization, and biological interpretation
- Demonstrated experience building end-to-end bioinformatics pipelines from scratch using reproducible workflow management frameworks (e.g., Nextflow, Snakemake, WDL, or equivalent)
- Experience with additional omics data types (ATAC-seq, proteomics, spatial transcriptomics, etc.) is a strong plus
- Proficiency in Python and R for bioinformatics analysis and tool development; experience with pipeline languages and shell scripting
- Experience building scientist-facing applications or dashboards (e.g., Shiny, Streamlit, Dash) for interactive data exploration
- Strong foundation in multivariate statistics and applied mathematics; familiarity with DoE methodology
- Familiarity with machine learning approaches applied to biological data — clustering, classification, dimensionality reduction
- Working knowledge of SQL or similar database platforms
- Excellent communication skills — able to present complex analytical findings clearly to both scientific and non-technical audiences
- Effective individual contributor and collaborative team member
Pay: $100,000.00 - $120,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Health insurance
- Life insurance
- Paid parental leave
- Paid time off
- Retirement plan
- Vision insurance
Work Location: In person