Director, R&d Neuroscience Data Science & Digital Health – Ophthalmology

What you'd actually do

1. Drive the development and application of advanced AI/ML methods, including cutting-edge computer vision techniques applied to ophthalmic imaging data (e.g., Optical Coherence Tomography and fundus images), to uncover disease mechanisms and identify novel biomarkers.
2. Lead the development and validation of novel digital endpoints. Engage with regulatory stakeholders to ensure these innovations enhance clinical trial design, improve patient monitoring and care pathways, and meet regulatory requirements.
3. Develop and apply sophisticated statistical models using real-world and clinical data to generate insights into disease progression, treatment outcomes, and patient stratification. Leverage longitudinal disease modeling, Bayesian methodologies, and causal inference techniques to inform decision-making.
4. Apply emerging generative AI approaches to boost data analysis and knowledge discovery, integrating diverse multimodal datasets (imaging, clinical, wearable, etc.) for a more holistic understanding of ophthalmic diseases.
5. Partner with Clinical Development and Medical Affairs to integrate RWE into evidence generation strategies. Support trial optimization and regulatory submissions by incorporating insights from large-scale clinical datasets, electronic health records (EHRs), and other real-world data sources.

Skills

What the JD emphasized

• AI/ML methods
• computer vision
• digital health
• ophthalmology
• clinical development
• regulatory requirements
• multimodal datasets
• real-world evidence

Other signals

• AI/ML methods
• computer vision
• digital health
• drug discovery
• clinical trial execution
• patient stratification
• digital biomarkers
• generative AI
• multimodal integration
• real-world evidence