What are the responsibilities and job description for the Computational Scientist position at Powerhouse Biology?
About Powerhouse Biology, Inc.
Powerhouse Biology, Inc. is a venture-backed biotechnology company. We are pioneering precision peptide therapeutics to address mitochondrial dysfunction, an underlying driver of many age-related diseases. Leveraging AI-guided multi-modal analysis, we develop cutting-edge therapeutics that restore mitochondrial function with unprecedented precision.
Join a fast-moving startup tackling one of biology’s biggest challenges: advancing healthy human lifespan. Work at the intersection of systems biology, synthetic biology, and machine learning, collaborate with creative and bright minds, and build systems that directly impact therapeutic development. If you thrive in a high-impact, no-nonsense environment where we innovate together to drive results, we want you on our team!
The role
We are seeking a creative and bright Computational Scientist to build and scale our computational frameworks for therapeutic discovery, with a specific focus on multi-modal biological data integration. They will lead the development of scalable, data-driven frameworks that connect complex biological networks to actionable therapeutic targets, tackling a core challenge in translating complex, multi-modal data into precision treatments for mitochondrial dysfunction.
This is a hands-on role: you will write production-quality code, contribute to core data infrastructure, and implement modeling frameworks. You’ll work across domains - data engineering, systems biology, and machine learning - to shape how we model complex disease mechanisms and prioritize therapeutic targets. The ideal candidate is not only a capable software developer but also a systems thinker who thrives on scientific abstraction and biological interpretability.
We will consider candidates who meet all of the following criteria:
- A degree in physics, applied mathematics, engineering, or a closely related quantitative discipline.
- At least 2 years of recent, full-time industry experience in a hands-on coding role in computational biology.
- Demonstrated experience working with RNA-seq datasets at scale in an independent or lead capacity.
- Hands-on experience with network models in systems biology, including building, analyzing, and interpreting biological graphs.
Key responsibilities
- Develop and maintain computational infrastructure to support AI-driven therapeutic discovery.
- Design and implement network models for determining causal mechanisms of mitochondrial function and dysfunction.
- Build scalable data pipelines for integrating multi-modal biological datasets.
- Ensure robust version control and collaborative development workflows.
- Optimize computational workflows for efficiency, reproducibility, and scalability.
- Work closely with biologists, chemists, and AI scientists to translate computational insights into real-world therapeutics.
Who you are
- Proficient in Python, with at minimum 2 years of hands-on experience in scientific computing and/or machine learning frameworks, ideally in industry.
- Skilled with network modeling, graph algorithms, and/or computational approaches to systems biology.
- Demonstrated expertise working with at minimum one type of omics dataset in an independent or lead capacity, such as driving analysis pipelines, integrating multi-omics data, or publishing results.
- Experienced in software development best practices, including version control (e.g. Git), code review, testing frameworks, workflow managers (e.g. Nextflow, Snakemake), and CI/CD pipelines.
- Comfortable working in a collaborative, interdisciplinary environment, integrating computational methods with experimental biology.
- Able to balance research and engineering, delivering robust computational tools while exploring novel methodologies.
- Effective at communicating in multi-disciplinary teams where you are simultaneously the expert and the apprentice.
Bonus qualifications
- Experience with AI/ML approaches in computational biology.
- Familiarity with cloud computing and high-performance computing environments.
- Experience working with imaging data and multi-modal datasets.
- Knowledge of mitochondrial biology.