DescriptionWe are seeking a postdoctoral fellow to focus on time-series modeling and wearable/mobile health data in the context of women’s health. The fellow will design and evaluate AI methods for high-frequency, longitudinal, and real-world data streams, with the goal of enabling translational insights in collaboration with clinicians and data scientists.
ResponsibilitiesDevelop and refine machine learning methods for wearable, mobile health, and longitudinal data.Design robust approaches to handle missingness, irregular sampling, and multimodal integration.Collaborate with clinical partners to ensure models are interpretable and clinically actionable.Lead manuscripts, presentations, and contributions to open-source pipelines.QualificationsRequirements
PhD in computer science, biomedical informatics, electrical engineering, statistics, or related field.Strong expertise in time-seri...