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This course presents quantitative models of biological systems rooted in statistical mechanics and polymer theory. Core topics include Brownian motion and Langevin dynamics; reaction-diffusion and pattern formation; first-passage processes; polymer physics and phase separation; and machine-learning applications in biology. Students will learn analytical theory, numerical algorithms, and coarse-grained simulations to address problems in quantitative biology. Prerequisites: Calculus; Linear Algebra; Differential Equations; Statistical Mechanics; basic proficiency in Python or MATLAB.