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  <title>CompChem Observer — newly added enhanced sampling events</title>
  <link href="https://compchem.observer/topics/enhanced-sampling.xml" rel="self"/>
  <link href="https://compchem.observer"/>
  <id>https://compchem.observer/topics/enhanced-sampling/</id>
  <updated>2026-09-28T15:41:52Z</updated>
  <author>
    <name>CompChem Observer</name>
  </author>
  <entry>
    <title>40th Molecular Simulation Symposium</title>
    <link href="https://compchem.observer/events/40th-molecular-simulation-symposium-2026/"/>
    <id>https://compchem.observer/events/40th-molecular-simulation-symposium-2026/</id>
    <updated>2026-09-28T00:00:00Z</updated>
    <summary>The 40th Molecular Simulation Symposium, organized by the Society for Molecular Simulation, will take place December 7-9, 2026, at Kyushu University Medical School Centennial Hall. It is co-organized with the Japan Society for Molecular Science.</summary>
  </entry>
  <entry>
    <title>Self-assembly of materials: merging direct experiments with simulations at different resolutions and data science techniques</title>
    <link href="https://compchem.observer/events/self-assembly-of-materials-merging-direct-experiments-with-simulations-at-different-resolutions-and-data-science-techniques-2027/"/>
    <id>https://compchem.observer/events/self-assembly-of-materials-merging-direct-experiments-with-simulations-at-different-resolutions-and-data-science-techniques-2027/</id>
    <updated>2026-09-28T00:00:00Z</updated>
    <summary>Workshop on self-assembly of materials, merging experiments with multi-scale simulations and data science techniques to bridge synthesis and modeling.</summary>
  </entry>
  <entry>
    <title>From Data to Dynamics: Machine Learning in Statistical Mechanics and Molecular Simulations</title>
    <link href="https://compchem.observer/events/ml-statistical-mechanics-molecular-simulation-2026/"/>
    <id>https://compchem.observer/events/ml-statistical-mechanics-molecular-simulation-2026/</id>
    <updated>2026-09-20T00:00:00Z</updated>
    <summary>How machine learning is changing molecular simulation in practice: learning collective variables, analysing the large trajectory datasets long runs now produce, and reaching biological timescales through enhanced sampling and coarse-graining.</summary>
  </entry>
  <entry>
    <title>MolSim 2027</title>
    <link href="https://compchem.observer/events/molsim-2027/"/>
    <id>https://compchem.observer/events/molsim-2027/</id>
    <updated>2026-09-20T00:00:00Z</updated>
    <summary>A two-week school that builds molecular simulation up from statistical mechanics, pairing lectures with hands-on sessions on simple model systems. Aimed at PhD students and postdocs in physics, chemistry and biology.</summary>
  </entry>
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