To ensure optimal mission training and readiness, scientists must not only create novel sensing and assessment technologies (e.g., wearable sensors for cognitive fatigue assessment), but also figure out how to aggregate, analyze and deliver information back to users and supervisors for decision-making.  In short, if the information being gathered and interrogated by monitoring and assessment technologies is not ‘actionable’, then it is not useful.  The aim of AFRL’s Signature Tracking for Optimized Nutrition and Training (STRONG) lab is to fill this gap through the assimilation of multivariate monitoring modalities (e.g., wearables, surveys, validated phys/cog performance tests, biomarker panels, sleep tracking etc.), big data analytics (e.g., neural networks, machine learning, nonlinear forecasting, etc.), and accessible feedback/augmentation technologies (e.g., visualization dashboards, personalized training/nutrition prescriptions, performance predictions, etc.).  In the end, the lab’s goal is to make a series of scientific and technological advancements in each of these areas that lead to tangible products (e.g., nutritional supplements, mobile phone/watch apps, wearable sensors, etc.) used to optimize human performance.  The current opportunity focuses on advancing research in any of three primary focus areas: 1) improved multivariate sensor analytics for performance prediction, 2) personalized nutrition and physical training prescription using artificial intelligence, and 3) innovative lab and field tools for rapid cognitive and physical performance assessment.