POSITION SUMMARY:
Natera, a leader in personalized genetic testing and diagnostics, is seeking a Director of Clinical Artificial Intelligence (ClinAI) to lead our program developing and deploying artificial intelligence (AI) and machine learning (ML) to advance the field of clinical diagnostics. This key role is centered on guiding research and development efforts aimed at improving cancer detection, treatment planning, and monitoring through cutting-edge AI solutions. The successful candidate will possess a robust blend of technical expertise in AI/ML and an understanding of its clinical applications in oncology, reproductive medicine, and organ health.
PRIMARY RESPONSIBILITIES:
- Leadership and Strategic Direction:
- Provide strategic leadership for the Clinical AI team, crafting and executing a vision for AI-driven innovations in diagnostics and therapeutics. Collaborate with cross-functional teams, including translational sciences, R&D, medical affairs, program management, and software development, to design and deploy AI models that enhance diagnostic, prognostic, and therapeutic accuracy & efficiency.
- Clinical Large-Language Models (LLMs):
- Spearhead the optimization and/or creation of biological models to generate insights into disease mechanisms, predict outcomes, and enhance therapeutic design. Additionally, oversee the use of LLMs to efficiently extract critical information from electronic health records, clinical trial data, and scientific publications, enhancing the foundation for diagnostic and treatment decisions.
- Genomic & Multi-Omics Data Analysis:
- Direct projects that apply ML algorithms for the examination of tumor genetic data, aiming to identify critical mutations and biomarkers that inform personalized treatment approaches. Guide the integration of various "omics" data sources (genomics, proteomics, metabolomics) using AI to achieve a holistic view of cancer biology, opening up new avenues for diagnostic markers and treatment targets.
- Pathology Image Analysis:
- Lead the development of AI algorithms to enhance digital pathology analysis, focusing on cancer cell detection, tumor grading, and heterogeneity analysis, to support accurate and detailed diagnostics.
- Predictive Modeling & Risk Stratification:
- Manage the creation of sophisticated models that integrate diverse data sets (clinical, imaging, molecular) to predict treatment outcomes, side effects, forecast disease progression, and optimize patient management. Lead efforts to develop algorithms for accurately stratifying patients by cancer risk, thereby optimizing screening and early detection strategies.
QUALIFICATIONS:
- Ph.D. or equivalent in Computer Science, Bioinformatics, Computational Biology, or a related discipline, with a focus on artificial intelligence , machine learning, and statistics.
- A minimum of 7 years of relevant experience in AI/ML research and development, particularly in oncology or healthcare applications, with a proven track record of leading projects from inception to clinical implementation.
- Extensive knowledge of oncology clinical practices, including diagnostics, genomics, and therapeutic strategies.
- Proficiency in AI/ML programming languages and frameworks (e.g., Python, R, TensorFlow, PyTorch, LLMs).
- Strong leadership skills, excellent communication abilities, and a knack for fostering collaboration across diverse scientific and clinical teams.
