Veracyte is looking to develop new diagnostic products by leveraging their extensive clinical cancer database, which includes multi-platform digital pathology, genomic, and clinical outcome data. The goal is to employ AI/ML to analyze this data, specifically whole-slide images (WSIs), to predict clinical and pathological outcomes, thereby transforming cancer care.
Requirements
- Expert in Python or equivalent language for AI/ML development in the context of computer vision / DPAI (this includes data manipulation and preparation.)
- Proficient in statistical analysis, especially in survival modelling and hypothesis testing (i.e., multivariate regression modelling with interaction effects).
- Experience working in cloud computing environments (AWS preferred).
- Demonstrated proficiency in summarizing and communicating findings from data, including an attention to detail when sharing findings.
- Knowledge of cancer biology
- Proficiency with documentation and submission in regulated diagnostic environments (LDT or IVD).
- Experience working with real world clinical data.
Responsibilities
- Develop digital pathology AI (DPAI) models with WSI data to predict clinical outcome and pathological/morphologic features, including adapting open-source state-of-the-art AI foundation models to Veracyte’s data.
- Evaluate and analyze DPAI models with respect to clinical, pathological and genomic outcomes or features, with a view to linking explainability of model features to biology.
- Collaborate with both internal and external partners to understand the clinical and business requirements for given products and tailor algorithms accordingly.
- Work with bioinformatician, statistician, and medical experts to document projects, including generating analyses and visualizations for publication in peer-reviewed journals.
- Apply and adapt state-of-the-art vision/vision-language foundation models to whole-slide images (WSIs).
- Show technical leadership in the field of digital pathology AI.
- Independently drive project execution and completion.
Other
- PhD in Data Science, Machine Learning, Applied Math or equivalent field.
- 8+ years of experience of data/applied scientist role or equivalent
- Ability to explain AI/ML concepts to both experts and non-experts, including formal presentation, academic writing, and generation of publication-quality figures.
- Passionate about data, eager to learn independently, and possesses strong analytical, problem-solving, and storytelling skills.
- Ability to work effectively in a fast-paced and collaborative environment.
