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Explore machine learning applications in materials science, focusing on innovative discovery techniques and computational advancements in the field.
Explore lattice dynamics through an in-depth seminar, gaining insights into crystal structures and their vibrational properties from expert Prof. Bartomeu Monserrat.
Explore the AdS/CFT correspondence for scalar field theory in lattice AdS_2 and AdS_3, delving into advanced concepts in theoretical physics and string theory.
Explore computational methods for studying correlated electron materials, focusing on advanced concepts and techniques in materials science and chemistry.
Explore computational methods for predicting material structures, focusing on advanced techniques and their applications in materials science.
Explore computational condensed matter using first principles thermodynamics, gaining insights into advanced techniques and applications.
Explore phi^4 theory and Ising model on spherical geometry, gaining insights into advanced physics concepts and their applications.
Explore quantum chromodynamics spectroscopy, delving into the study of hadron properties and interactions through advanced theoretical and computational methods.
Explore phonons and structural transitions using DFT and group theory, gaining insights into fundamental concepts and advanced computational techniques.
Explore phonons and structural transitions using DFT and group theory, advancing understanding of material properties and phase changes.
Learn essential data management principles for research, including tools, metadata, and FAIR practices. Enhance project organization and efficiency.
Explore GPU computing and Krylov solvers for advanced numerical computations, enhancing problem-solving skills in high-performance computing environments.
Explore exascale computing, HPC architectures, and GPU programming with Dr. Meifeng Lin from Brookhaven National Laboratory.
Explore quantum computing fundamentals, including qubits, superposition, and entanglement. Gain insights into potential applications and future implications of this revolutionary technology.
Explore machine learning applications in crystallization, from molecular dynamics to enhanced sampling techniques for rare events and homogeneous nucleation.
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