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Cancer detection company enabling people at risk for high-mortality cancers to live longer, healthier lives.
The Role
Develops bioinformatics algorithms and machine learning models to detect early-stage cancer from cell-free DNA and epigenomic data. Responsibilities include experimental design, clinical genomics analysis, statistical modeling, software tool evaluation, production-ready coding, and communicating findings to cross-functional teams. The role requires strong computational biology, statistical learning, programming, and genomics expertise, with opportunities to use deep learning, SQL, and AWS.
Summary Generated by Built In
ClearNote Health is an early cancer detection company focused on the development and commercialization of non-invasive epigenomic tests to detect cancer through a standard blood draw, earlier than existing methods and when the disease is still treatable. Leveraging its novel liquid biopsy technology, ClearNote Health is initially focused on high-mortality cancers with the greatest need for early detection, starting with pancreatic and ovarian cancers.
Position Summary:
We are seeking a Bioinformatics Scientist I/II/Senior to play a pivotal role in designing algorithms to identify early-stage cancer in cell free DNA from plasma.
In this high-impact position, you will work as part of a collaborative team to analyze epigenomic and genomic features from cell free DNA and develop classification algorithms for early cancer detection. You’ll contribute across the full lifecycle—from experimental design and data analysis to production-ready code and results presentation to cross-functional teams.
Key Responsibilities:
Position Summary:
We are seeking a Bioinformatics Scientist I/II/Senior to play a pivotal role in designing algorithms to identify early-stage cancer in cell free DNA from plasma.
In this high-impact position, you will work as part of a collaborative team to analyze epigenomic and genomic features from cell free DNA and develop classification algorithms for early cancer detection. You’ll contribute across the full lifecycle—from experimental design and data analysis to production-ready code and results presentation to cross-functional teams.
Key Responsibilities:
- Design and analyze experiments using ClearNote’s epigenomics platform
- Develop and apply machine learning techniques tailored to the platform’s unique data characteristics
- Analyze clinical genomics data to train models that make clinically relevant predictions (e.g., cancer detection from epigenomic profiles)
- Apply appropriate statistical methods to support rigorous, scientifically sound decision-making
- Evaluate and recommend software tools for epigenomic data analysis
- Write clean, maintainable code following software engineering best practices
- Present findings clearly, concisely, and quantitatively to cross-functional stakeholders
- Communicate hypotheses, data insights, and experimental designs to colleagues, collaborators, and advisors
- Embody and uphold ClearNote’s core values—visionary, pioneering, truth-seeking, driven, honest and considerate communication, and a commitment to diversity—while operating with transparency and integrity
- PhD or equivalent experience in Biophysics, Genetics, Genomics, Biochemistry, Molecular Biology, or a related field with a strong computational focus
- Experience working with genomics technologies, preferably with cell free DNA
- Ability to interpret biological data quantitatively using principles of molecular biology and biochemistry
- Proficiency in statistical methods for supervised machine learning including logistic regression, random forest, and XGBoostExperience developing neural network models, particularly multi-layer perceptrons (MLPs)
- Familiarity with deep learning approaches for genomic/epigenomic data (e.g., DNA sequence models or foundation models) is a plus
- Understanding of common parametric and non-parametric statistical tests
- Strong programming skills in Python and/or R
- Experience using Git for version control in a collaborative environment (branching, merging, pull requests)
- Strong communication skills — both written and verbal — with the ability to explain complex concepts to cross-functional teams
- Experience with relational databases and SQL is a plus
- Experience with AWS services, particularly EC2 and Batch, is a plus
Skills Required
- PhD or equivalent experience in biophysics, genetics, genomics, biochemistry, molecular biology, or a related field with a strong computational focus
- Experience working with genomics technologies
- Experience with cell-free DNA technologies
- Ability to interpret biological data quantitatively using molecular biology and biochemistry principles
- Proficiency with supervised machine learning methods, including logistic regression, random forest, and XGBoost
- Experience developing neural network models, particularly multi-layer perceptrons
- Familiarity with deep learning approaches for genomic or epigenomic data
- Understanding of parametric and non-parametric statistical tests
- Strong programming skills in Python and/or R
- Experience using Git for collaborative version control, including branching, merging, and pull requests
- Strong written and verbal communication skills, including explaining complex concepts to cross-functional teams
- Experience with relational databases and SQL
- Experience with AWS services, particularly EC2 and Batch
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The Company
What We Do
ClearNote Health – Cancer detection company enabling people at risk for high-mortality cancers to live longer, healthier lives. We focus on developing non-invasive tests to detect cancer through a standard blood draw earlier than existing methods by harnessing the power of epigenomics. We apply our proprietary epigenomic platform, combining biology and artificial intelligence, to identify DNA-based changes in biology as cancer develops. With lead programs in non-invasive early detection of pancreatic and ovarian cancers in patients at the highest risk for these diseases. Headquartered in the U.S, the company’s CLIA and CAP-accredited laboratory is located in San Diego, Calif., with additional presence in the San Francisco Bay Area and internationally. #biotechnology #epigenomics #oncology #cancerresearch #cancer
