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Day 9-11 Machine Learning Interatomic Potentials
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    • Introduction to Work Environment
    • Day 1-2: Introduction to Modern Fortran
    • Day 1-2: Introduction to Python
    • Day 3: Statistical Mechanics Problems
    • Day 4 Monte Carlo integration
    • Day 4 Monte Carlo at Constant Pressure
    • Day 5 Introduction to Molecular Dynamics
    • Day 5 Phase equilibria
    • Day 6 Stability and Accuracy of Molecular Dynamics
    • Day 6 Constraints: Multiple timesteps and RATTLE
    • Day 8 Force-fields, potentials and optimisation methods
    • Day 8 MD Ensembles: NVE and NVT
    • Day 9: Setup environment for advanced courses
    • Day 9-11 Mesoscale: Introduction
    • Day 9 Mesoscale: DPD Tutorial Exercise 1: Simple DPD systems
    • Day 9 Mesoscale: DPD Tutorial Exercise 2: Applying DPD to molecular systems
    • Day 10 Mesoscale: LBE Tutorial Exercise 1: Single component LBE simulations
    • Day 11 Mesoscale: LBE Tutorial Exercise 2: Multi-Component LBE simulations
    • Day 9-11: First principles: CRYSTAL Tutorials
    • Day 9: First Principles: Castep Simulation
    • Day 9-11: First Principles: Phonons and Spectroscopy Tutorial
    • Day 10: Band Structure and DOS Calculation of ZnS
    • Day 9-11 Machine Learning Interatomic Potentials
      • extra tutorials
    • Day 9-11 Biomolecular simulations
    • Day 11: First principles: BigDFT Tutorials
    • Appendix A: Plotting “.csv” files with gnuplot
    • Appendix B: The Boltzmann Equation - an outline derivation
    • Appendix C: Outline Notes on Fluid Mechanics
    • extra tutorials

    Day 9-11 Machine Learning Interatomic Potentials¶

    retrieve the tutorials from the github by cloning into the jupyterhub account.

    git clone https://github.com/imagdau/Tutorials

    extra tutorials¶

    • https://projects.volkamerlab.org/teachopencadd/all_talktorials.html

    • https://projects.volkamerlab.org/teachopencadd/talktorials/T035_graph_neural_networks.html

    • https://projects.volkamerlab.org/teachopencadd/all_talktorials.html

    • https://lightning.ai/docs/pytorch/stable/tutorials.html

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