Explore the theoretical and computational foundations of complex systems through this intensive college program that examines how large numbers of interacting components give rise to emergent collective behaviors across physics, biology, engineering, and economics. Delve into five comprehensive lecture series covering optimization, inference and learning in biological systems, random matrix theory and applications, thermodynamics and out-of-equilibrium dynamics in disordered systems, and quantitative bacterial physiology. Master the statistical and quantum physics tools essential for analyzing complex systems through 45 detailed lectures delivered by leading researchers from prestigious institutions including SISSA Trieste, ENS Paris, University of Rome La Sapienza, University of Waterloo, and King's College London. Gain hands-on experience with cutting-edge research methodologies while developing quantitative analysis skills applicable to diverse fields ranging from biological networks to economic systems. Prepare for advanced research in complex systems physics through structured learning that culminates in comprehensive written assessments designed to test your understanding of these interconnected theoretical frameworks.

Syllabus

Optimization, inference and learning in biological systems - Lecture 1
Optimization, inference and learning in biological systems - Lecture 2
Random Matrices: Theory and Practice - Lecture 1
Optimization, inference and learning in biological systems - Lecture 3
Random Matrices: Theory and Practice - Lecture 2
Random Matrices: Theory and Practice - Lecture 3
Optimization, inference and learning in biological systems - Lecture 4
Optimization, inference and learning in biological systems - Lecture 5
Random Matrices: Theory and Practice - Lecture 4
Optimization, inference and learning in biological systems - Lecture 6
Random Matrices: Theory and Practice - Lecture 5
Random Matrices: Theory and Practice - Lecture 6
Optimization, inference and learning in biological systems - Lecture 7
Optimization, inference and learning in biological systems - Lecture 8
Thermodynamics and out of equilibrium dynamics in disordered systems - Lecture 1
Optimization, inference and learning in biological systems - Lecture 9
Thermodynamics and out of equilibrium dynamics in disordered systems - Lecture 2
Thermodynamics and out of equilibrium dynamics in disordered systems - Lecture 3
Thermodynamics and out of equilibrium dynamics in disordered systems - Lecture 4
Quantitative Bacterial Physiology - Lecture 1
Random Matrices: Theory and Practice - Lecture 7
Quantitative Bacterial Physiology - Lecture 2
Random Matrices: Theory and Practice - Lecture 8
Quantitative Bacterial Physiology - Lecture 3
Thermodynamics and out of equilibrium dynamics in disordered systems - Lecture 5
Quantitative Bacterial Physiology - Lecture 4
Quantitative Bacterial Physiology - Lecture 5
Random Matrices: Theory and Practice - Lecture 9
Quantitative Bacterial Physiology - Lecture 6
Quantitative Bacterial Physiology - Lecture 7
Quantitative Bacterial Physiology - Lecture 8
Thermodynamics and out of equilibrium dynamics in disordered systems - Lecture 6
Quantitative Bacterial Physiology - Lecture 9
Thermodynamics and out of equilibrium dynamics in disordered systems - Lecture 7
Thermodynamics and out of equilibrium dynamics in disordered systems - Lecture 8
Thermodynamics and out of equilibrium dynamics in disordered systems - Lecture 9