Sort by
Refine Your Search
-
quantitative predictions testable against empirical data from diverse ecological contexts. We use methods from theoretical evolutionary biology, including optimal control theory, life history modelling, adaptive
-
-Service (MaaS) ecosystem. The work will integrate deep reinforcement learning, autonomous agent modelling, and multi-objective optimization to enable predictive simulation, real-time resource management
-
to brain disorders, uncovering mechanistic pathways, and identifying therapeutic targets and disease predicting biomarkers. We develop and apply human-based disease models to advance understanding of brain
Enter an email to receive alerts for model-predictive-"https:" positions