Scientist, Computational Biology
Skills
- Hands-on experience analyzing -omics data using R and/or Python
- Proficiency with modern ML frameworks (PyTorch required; TensorFlow a plus)
- Knowledge of statistical inference and machine-learning methods (random forests, SVMs, neural networks, transformers)
- Experience with reproducible software practices: version control, containers, documented pipelines
- Familiarity with NGS technologies and experimental biology workflows
- Ability to design experiments computationally (power analysis, Bayesian planning)
- Strong written and verbal communication and cross-functional collaboration skills
Responsibilities
- Develop computational methods to interrogate signals from extracellular vesicles and other minimally invasive biospecimens
- Perform multi-omic analyses (single-cell and bulk RNA-seq, proteomics) and integrate public and proprietary datasets
- Design and analyze wet-lab experiments, including power analyses and Bayesian experiment planning
- Build and maintain reproducible analysis pipelines, annotated code repositories, and containerized environments
- Coordinate experiments and data exchange with CROs and external collaborators
- Communicate results through written reports and oral presentations to internal teams and partners
- Help hire, mentor, and grow the computational team
Education
- PhD in computational biology, systems biology, bioinformatics, computer science, or related field
- Postgraduate research or industry experience in multi-omic data analysis preferred
Benefits
- Competitive salary and equity participation in an early-stage company
- Comprehensive health, dental, and vision insurance
- Paid time off and flexible leave policies
- Professional development and conference support
- Collaborative, mission-driven company culture
Average salary estimate
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