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SUMMARY:PWF Uzbekistan: The Second School on Materials Modeling and Simula
 tion
DTSTART;VALUE=DATE-TIME:20261116T030000Z
DTEND;VALUE=DATE-TIME:20261121T130000Z
DTSTAMP;VALUE=DATE-TIME:20261112T061411Z
UID:indico-event-11561@ictp.it
DESCRIPTION:About The School\nAtomistic simulations have become essential 
 tools for understanding and predicting the properties of materials. Molecu
 lar dynamics (MD) provides a powerful framework for investigating the stru
 ctural\, thermal\, and mechanical behavior of materials at the atomic scal
 e. However\, conventional empirical interatomic potentials often face limi
 tations in accuracy and transferability\, while first-principles calculati
 ons remain computationally expensive for large systems and long simulation
  times.\nRecent advances in machine-learning interatomic potentials (MLIPs
 ) are opening new possibilities for materials modeling by combining the ac
 curacy of first-principles reference calculations with the computational e
 fficiency required for large-scale atomistic simulations.\nFollowing the f
 irst PWF Uzbekistan School on Materials Modeling and Simulation held in Na
 mangan in October 2025\, this second school will focus on machine-learning
 -accelerated molecular dynamics\, emphasizing both fundamental concepts an
 d practical computational approaches.\nThe six-day programme will combine 
 introductory lectures\, hands-on tutorials\, and guided computational exer
 cises. Participants will learn the fundamentals of molecular dynamics\, ex
 plore essential machine-learning concepts\, and gain practical experience 
 in training\, validating\, and applying machine-learning interatomic poten
 tials.\nThe school will introduce widely used computational tools\, includ
 ing LAMMPS and GPUMD\, with particular attention to Neuroevolution Potenti
 als (NEP) and their applications in materials science.Main Topics\n		Funda
 mentals of molecular dynamics and interatomic potentials\n	\n		Introductio
 n to machine learning for atomistic simulations\n	\n		Atomic descriptors a
 nd neural-network interatomic potentials\n	\n		Preparation of reference da
 tasets and training of machine-learning potentials\n	\n		Validation and as
 sessment of machine-learning potentials\n	\n		Molecular dynamics simulatio
 ns using LAMMPS and GPUMD\n	\n		Applications to structural\, thermal\, and
  mechanical properties of materials\n	\n		Guided computational exercises a
 nd student mini-projects\n\n	 \nTarget Participants\nThe school is primar
 ily intended for advanced undergraduate and master’s students in physics
 \, materials science\, chemistry\, and related disciplines. Applications f
 rom early-career researchers interested in computational materials science
  are also welcome.\nThe school particularly encourages participation from 
 universities and research institutions in Uzbekistan and neighboring count
 ries\, including Tajikistan and Afghanistan.Prerequisites\nParticipants sh
 ould have a basic understanding of classical mechanics and elementary prog
 ramming concepts. Familiarity with Python\, Linux\, or atomistic simulatio
 n methods would be helpful but is not mandatory.\n	 \nTeaching Format\nTh
 e programme will combine theoretical lectures with practical computational
  sessions. Students will work with open-source scientific software and pre
 pared datasets to develop reproducible simulation workflows.\nParticipants
  will have opportunities to interact with lecturers\, discuss scientific p
 roblems\, and explore future research directions in computational material
 s science.Coordinators\n\n		Prof. S. Mehdi Vaez Allaei — University of T
 ehran\, Iran\; Norwegian University of Science and Technology (NTNU)\, Nor
 way\n	\n		Prof. Umedjon Khalilov — Arifov Institute of Ion-Plasma and La
 ser Technologies (IPLT)\, Uzbekistan\; University of Antwerp (UA)\, Belgiu
 m\nLocal Organizers\n\n		Prof. Abduvohid Safarov — Termez State Universi
 ty\, Uzbekistan\n	\n		Prof. Umedjon Khalilov — IPLT\, Uzbekistan\n	\n		D
 r. Azamat Narbayev — Termez State University\, Uzbekistan\nLecturers\n\n
 		Prof. S. Mehdi Vaez Allaei — University of Tehran\, Iran\; NTNU\, Norw
 ay\n	\n		Prof. S. Javad Hashemifar — Isfahan University of Technology\, 
 Iran\n	\n		Prof. Natasa Stojic — ICTP\, Italy\n	\n		Prof. Umedjon Khalil
 ov — IPLT\, Uzbekistan\; UA\, Belgium\n\n\n//indico.ictp.it/event/11561/
LOCATION:Termez State University\, Termez
URL://indico.ictp.it/event/11561/
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