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:
- 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
Qualifications:
- 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
The anticipated salary range for this position is $125,000 to $180,000. The actual salary will be dependent on various factors that may include experience level, knowledge, skills, and abilities.