ABOUT KARIUS

Karius is a venture-backed life sciences startup transforming the way pathogens and other microbes are observed throughout the body. By unlocking the information present in microbial cell-free DNA, we’re helping doctors quickly solve their most challenging cases, accelerating industry partners’ biomarker discovery and clinical trials, uncovering novel microbes, and ultimately working to reduce patient suffering worldwide.

POSITION SUMMARY

You are curious, creative, and driven to make a meaningful impact on patients. As a key member of the Computational Biology team, you will develop and improve algorithms that are central to maximizing the value of our data. You’ll operate at the cutting edge of computational biology, collaborating across disciplines to solve complex problems and innovate where existing solutions fall short. This role is ideal for a self-starter who thrives in a fast-paced, mission-driven environment and has a passion for scientific rigor and quality.

TRAVEL REQUIREMENTS

• Ability to travel to HQ once per quarter for team events, if remote.

PHYSICAL REQUIREMENTS

• Subject to extended periods of sitting and/or standing, and moderate noise levels. Work is generally performed in an office environment.

POSITION REQUIREMENTS

• Ph.D. or Masters in computer science, statistics, mathematics, physics, or a related field, preferably with a focus on computational biology.
• Proven experience in biotech, pharma, or relevant industry settings: minimum required experience with PhD is 2+ years, Masters is 5+ years.
• Demonstrated track record of developing novel quantitative models for biological data, as shown through relevant publications.
• Experience with probabilistic models (e.g., Dirichlet processes).
• Expertise with NGS/bioinformatics, statistics, and machine learning tools for analysis of high-dimensional datasets.
• Experience in diagnostics is highly desirable.
• Excellent communication skills and ability to thrive in collaborative, cross-functional teams.
• Comfortable working in a small, agile team where responsibilities span both research and development, and able to shift focus as needed to meet evolving project goals.

PERSONAL QUALIFICATIONS

• Passionate and purpose-driven with a deep connection to Karius’ mission.
• Comfortable in a hybrid research-development environment.
• Detail-oriented, organized, and effective in a fast-paced startup setting.
• Eager to grow and help others grow as part of a collaborative, learning-focused team.
• Strong scientific curiosity and a drive to solve complex biological problems through data.
• Adaptable and resilient in the face of ambiguity and evolving priorities.
• Committed to scientific integrity, transparency, and rigor in every aspect of work.
• Excellent communicator who can translate technical insights into actionable biological understanding.

DISCLAIMER

The above job description is intended to describe the general nature and level of work being performed by individuals assigned to this position. It is not intended to be an exhaustive list of all duties, responsibilities, and skills required. Responsibilities and duties may change or be adjusted to meet the needs of the company, and additional duties may be assigned as necessary. The job description is subject to change at any time at the discretion of Karius.

• Develop, implement, validate and improve novel computational methods and algorithms to extract actionable insights from high-dimensional biological data.
• Implement and optimize computational pipelines for analyzing complex, high-dimensional NGS and other biological datasets.
• Collaborate cross-functionally with colleagues in Assay Development, Analytics, Research, Engineering, Molecular Biology, and Medical Affairs to understand data properties, clinical context, and opportunities for improvement.
• Drive data interpretation and biological contextualization of findings, contributing to publications, presentations and regulatory submissions.
• Stay current on emerging trends in computational biology, metagenomics, statistics, and software engineering, and proactively apply relevant advances to enhance analytical capabilities and scientific rigor.
• Explore diverse approaches to modeling and problem-solving across quantitative disciplines.
• Share a passion for ensuring the quality of our computational methods.