retrieve:
Return the details about the given Memento id.

list:
List all Memento objects.

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Content-Type: application/json
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            "id": 70957,
            "title": "From Data to Dynamics: Machine Learning in Statistical Mechanics and Molecular Simulations",
            "slug": "from-data-to-dynamics-machine-learning-in-statis-2",
            "event_url": "https://memento.epfl.ch/event/from-data-to-dynamics-machine-learning-in-statis-2",
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            "start_date": "2026-10-14",
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            "description": "<p>You can apply to participate and find all the relevant information (speakers, abstracts, program,...) on the event website: <a href=\"https://www.cecam.org/workshop-details/from-data-to-dynamics-machine-learning-in-statistical-mechanics-and-molecular-simulations-1487\">https://www.cecam.org/workshop-details/from-data-to-dynamics-machine-learning-in-statistical-mechanics-and-molecular-simulations-1487</a>.<br>\r\n<br>\r\nRegistration is required to attend the full event, take part in the social activities and present a poster at the poster session (if any).  However, the EPFL community is welcome to attend specific lectures without registration if the topic is of interest to their research. Do not hesitate to contact the <a href=\"mailto:[email protected]\">CECAM Event Manager</a> if you have any question.<br>\r\n<br>\r\n<strong>Description</strong><br>\r\nSince its introduction in the 1970s, molecular dynamics (MD) has become an indispensable computational microscope for studying complex biological systems at atomic resolution. It has enabled detailed investigations into protein folding, conformational dynamics, and ligand binding and unbinding. Over the past decade, increasing computational power has made microsecond-scale simulations routine, producing massive datasets that demand sophisticated analysis strategies [1]. Despite these advances, conventional MD simulations still face a fundamental limitation: many biologically relevant events occur over milliseconds to seconds—timescales largely inaccessible to standard MD.<br>\r\nTo bridge this gap, researchers increasingly turn to enhanced sampling techniques—such as metadynamics and umbrella sampling [2,3]—and coarse-grained (CG) modeling approaches [4]. These methods enable more comprehensive exploration of the system’s free energy landscape, yet their success critically depends on the selection of appropriate reaction coordinates or collective variables (CVs). CVs must capture the slowest, most functionally relevant motions to accurately reflect thermodynamic and kinetic behavior. However, identifying suitable CVs remains one of the field’s most challenging tasks, typically requiring domain expertise and iterative refinement [5, 6].<br>\r\nThis complexity has fueled growing interest in machine learning (ML) techniques, which are now transforming how MD simulations are analyzed, interpreted, and even conducted. ML methods have been applied to automate CV discovery, perform dimensionality reduction, build thermodynamic and kinetic models, and enhance sampling efficiency [7]. These models often employ artificial neural networks or graph neural networks to map high-dimensional molecular configurations—such as Cartesian coordinates or molecular descriptors—into low-dimensional representations suitable for analysis [8].<br>\r\nDepending on the structure and type of data, ML algorithms can be broadly categorized into supervised, unsupervised, and reinforcement learning paradigms [9]. Supervised learning uses labeled input-output pairs to predict properties such as molecular energies or binding affinities [10], while unsupervised learning enables the identification of latent features, such as CVs, directly from data [11].<br>\r\nA cornerstone of modern ML-driven simulation is the development of symmetry-aware molecular representations. The predictive power of ML models hinges on encoding physical symmetries—like rotation and translation—directly into the model. E(3)-equivariant neural networks have emerged as powerful tools for this purpose, significantly improving data efficiency and generalization in learning potential energy surfaces [12]. Ongoing research continues to explore the optimal balance between enforcing strict symmetry and retaining model flexibility.<br>\r\nMeanwhile, breakthroughs in structural prediction—most notably the advent of AlphaFold 3—have revolutionized how researchers obtain initial molecular configurations. AlphaFold now provides remarkably accurate models of not only proteins but also their complexes with nucleic acids, ions, and small-molecule ligands [13]. However, these are static snapshots. They cannot capture dynamic behaviors, allosteric transitions, or binding kinetics—areas where physics-based simulations remain indispensable. Initial benchmarks suggest that even state-of-the-art predictors still fall short in modeling protein dynamics and ranking ligand binding affinities, further emphasizing the role of MD [14].<br>\r\nTo address the dimensionality and sampling bottlenecks, unsupervised ML approaches such as time-lagged autoencoders have reframed CV identification as a data-driven task. More recently, generative models—including diffusion models and variational autoencoders—have emerged as a new frontier. These models can learn the full conformational landscape of biomolecules and enable enhanced sampling, in some cases eliminating the need for predefined CVs altogether [15].<br>\r\nOnce accurate structural models and CVs are established, ML can significantly improve the estimation of thermodynamic and kinetic properties. In drug discovery, for instance, predicting protein–ligand binding affinity remains a central challenge. ML potentials trained on quantum mechanical data can be combined with enhanced sampling to yield highly accurate free energy landscapes and binding kinetics—results previously unattainable due to computational limitations [16]. However, challenges in data quality, model interpretability, and transferability remain critical areas of ongoing investigation [17].<br>\r\nFinally, ML is driving a renaissance in CG modeling. Deep neural networks can now learn many-body CG potentials directly from all-atom simulations, capturing emergent properties and enhancing transferability [18]. These models open the door to longer, larger-scale simulations with greater physical accuracy.<br>\r\nIn this rapidly evolving context, it becomes imperative to critically assess both the promise and limitations of ML in biomolecular simulation. The excitement surrounding these developments must be tempered by careful validation and benchmarking. This workshop thus serves as a timely opportunity—especially for early-career researchers—to explore these cutting-edge methods, engage in constructive dialogue, and chart new directions in the application of machine learning to molecular dynamics and drug discovery.<br>\r\n <br>\r\n<strong>References</strong><br>\r\n<br>\r\n<a href=\"https://doi.org/10.1103/physrevlett.98.146401\" target=\"_blank\">[1] J. Behler, M. Parrinello, Phys. Rev. Lett., <strong>98</strong>, 146401 (2007)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.sbi.2024.102972\" target=\"_blank\">[2] P. Sahrmann, G. Voth, Current Opinion in Structural Biology, <strong>90</strong>, 102972 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jcim.2c01127\" target=\"_blank\">[3] K. Kříž, L. Schmidt, A. Andersson, M. Walz, D. van der Spoel, J. Chem. Inf. Model., <strong>63</strong>, 412-431 (2023)</a><br>\r\n<a href=\"https://doi.org/10.3389/fmolb.2022.899805\" target=\"_blank\">[4] K. Ahmad, A. Rizzi, R. Capelli, D. Mandelli, W. Lyu, P. Carloni, Front. Mol. Biosci., <strong>9</strong>, (2022)</a><br>\r\n<a href=\"https://doi.org/10.1146/annurev-physchem-083122-125941\" target=\"_blank\">[5] S. Mehdi, Z. Smith, L. Herron, Z. Zou, P. Tiwary, Annual Review of Physical Chemistry, <strong>75</strong>, 347-370 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1101/2025.04.07.647682\" target=\"_blank\">[6] H. Zheng, H. Lin, A. Alade, J. Chen, E. Monroy, M. Zhang, J. Wang, AlphaFold3 in Drug Discovery: A Comprehensive Assessment of Capabilities, Limitations, and Applications, 2025</a><br>\r\n<a href=\"https://doi.org/10.1038/s41586-024-07487-w\" target=\"_blank\">[7] J. Abramson, J. Adler, J. Dunger, R. Evans, T. Green, A. Pritzel, O. Ronneberger, L. Willmore, A. Ballard, J. Bambrick, S. Bodenstein, D. Evans, C. Hung, M. O’Neill, D. Reiman, K. Tunyasuvunakool, Z. Wu, A. Žemgulytė, E. Arvaniti, C. Beattie, O. Bertolli, A. Bridgland, A. Cherepanov, M. Congreve, A. Cowen-Rivers, A. Cowie, M. Figurnov, F. Fuchs, H. Gladman, R. Jain, Y. Khan, C. Low, K. Perlin, A. Potapenko, P. Savy, S. Singh, A. Stecula, A. Thillaisundaram, C. Tong, S. Yakneen, E. Zhong, M. Zielinski, A. Žídek, V. Bapst, P. Kohli, M. Jaderberg, D. Hassabis, J. Jumper, Nature, <strong>630</strong>, 493-500 (2024)</a><br>\r\n[8] Fabian B. Fuchs, Daniel E. Worrall, Volker Fischer, Max Welling, NIPS'20: Proceedings of the 34th International Conference on Neural Information Processing Systems, Article No.: 166, Pages 1970 - 1981 (2020)<br>\r\n<a href=\"https://doi.org/10.1080/00268976.2020.1737742\" target=\"_blank\">[9] H. Sidky, W. Chen, A. Ferguson, Molecular Physics, <strong>118</strong>, (2020)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.sbi.2019.12.016\" target=\"_blank\">[10] Y. Wang, J. Lamim Ribeiro, P. Tiwary, Current Opinion in Structural Biology, <strong>61</strong>, 139-145 (2020)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41586-018-0337-2\" target=\"_blank\">[11] K. Butler, D. Davies, H. Cartwright, O. Isayev, A. Walsh, Nature, <strong>559</strong>, 547-555 (2018)</a><br>\r\n<a href=\"https://doi.org/10.1146/annurev-physchem-042018-052331\" target=\"_blank\">[12] F. Noé, A. Tkatchenko, K. Müller, C. Clementi, Annu. Rev. Phys. Chem., <strong>71</strong>, 361-390 (2020)</a><br>\r\n<a href=\"https://doi.org/10.1080/23746149.2021.2006080\" target=\"_blank\">[13] S. Kaptan, I. Vattulainen, Advances in Physics: X, <strong>7</strong>, (2022)</a><br>\r\n<a href=\"https://doi.org/10.1002/wcms.1455\" target=\"_blank\">[14] V. Limongelli, WIREs. Comput. Mol. Sci., <strong>10</strong>, (2020)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.chemrev.0c01195\" target=\"_blank\">[15] A. Glielmo, B. Husic, A. Rodriguez, C. Clementi, F. Noé, A. Laio, Chem. Rev., <strong>121</strong>, 9722-9758 (2021)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.sbi.2018.11.005\" target=\"_blank\">[16] A. Pak, G. Voth, Current Opinion in Structural Biology, <strong>52</strong>, 119-126 (2018)</a><br>\r\n<a href=\"https://doi.org/10.1021/jacs.6b05602\" target=\"_blank\">[17] M. Lelimousin, V. Limongelli, M. Sansom, J. Am. Chem. Soc., <strong>138</strong>, 10611-10622 (2016)</a><br>\r\n<a href=\"https://doi.org/10.3390/e16010163\" target=\"_blank\">[18] C. Abrams, G. Bussi, Entropy, <strong>16</strong>, 163-199 (2013)</a>\r\n</p><div class=\"active tab-pane\"> </div>",
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            "organizer": "<strong>Daniele Angioletti, </strong>Università della Svizzera Italiana (USI) ; <strong>Vincenzo Maria D'Amore, </strong>University of Naples \"Federico II\" ; <strong>Marco De Vivo, </strong>Istituto Italiano di Tecnologia ; <strong>Francesco Saverio Di Leva, </strong>University of Naples Federico II ; <strong>Vittorio Limongelli, </strong>Università della Svizzera Italiana USI Lugano ; <strong>Gregory Voth, </strong>University of Chicago",
            "contact": "<a href=\"mailto:[email protected]\"><strong>Cornelia Bujenita</strong></a>, CECAM Events and Operations Manager",
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            "title": "EPFL Latsis Symposium 2026: “Decoding the Cell: Modeling, Predicting, and Engineering Cellular States”",
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            "title": "Coding Club for Girls in Luzern",
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            "start_date": "2026-11-14",
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            "description": "<p>Eine App programmieren? Ein Computerspiel erfinden? Eine Animation gestalten?<br>\r\nWenn dich eines dieser Dinge interessiert, bist du hier am richtigen Ort! Tausche und teile deine Ideen, lerne zu programmieren und entdecke Informatikberufe.<br>\r\n<br>\r\nDie <a href=\"https://www.epfl.ch/education/education-and-science-outreach/de/jugendliche/coding-club/\">Coding Club for Girls</a> Workshops sind für Mädchen im Alter von 11 bis 15 Jahren und die Teilnahme ist kostenlos. Ab der Teilnahme an vier Workshops pro Jahr wird eine Teilnahmebestätigung ausgehändigt. <br>\r\n<br>\r\n<strong>Ort:</strong>  Kantonschule Musegg, Luzern<br>\r\n<br>\r\n<strong>Datum und Zeit:</strong><br>\r\n<strong>14. November 2026 : 09:30 bis 12:00 oder 13:30 bis 16:00 Uhr  // Hello 3D World<br>\r\n28. November 2026</strong><strong> : 09:30 bis 12:00 oder 13:30 bis 16:00 Uhr  // Webdesignerin</strong><br>\r\n<br>\r\nDie Inhalte der Workshops sind untenstehend beschrieben.<br>\r\n<br>\r\n<strong>Bedingungen</strong>\r\n</p><ul>\r\n\t<li>Gratis</li>\r\n\t<li><a href=\"https://forms.gle/ccrAC4MTpoEuBsqX8\">Anmeldung unter diesem Link </a></li>\r\n\t<li><a href=\"https://www.epfl.ch/education/education-and-science-outreach/de/teilnahmebedingungen/\">Allgemeine Teilnahmebedingungen EPFL - SPS Aktivitäten</a> </li>\r\n</ul>\r\n<strong>Workshops:<br>\r\nHello 3D World - 14. November 2026</strong><br>\r\nWie denkst du wurden die Figuren und Kulissen in den Filmen Shrek, Cars, Ice Age oder Kung Fu Panda gestaltet? Beim Entwerfen und Animieren von 3D-Objekten kannst Du wie im richtigen Animationsstudio gleichzeitig in die Rolle einer Künstlerin und einer Informatikerin schlüpfen. Du wirst dreidimensionale Objekte rund um das Thema Wald gestalten und in einem zweiten Schritt deiner Fantasie freien Lauf lassen und deine eigenen 3D-Objekte entwerfen!<br>\r\n<br>\r\n<strong>Webdesignerin - 28. November 2026</strong><br>\r\nEntdecke den Hintergrund einer Webseite und entwerfe deine eigene von A bis Z mit derselben Sprache wie die Profis! An diesem Workshop wirst du mit HTML vertraut und wirst verstehen, wie Webseiten gestaltet wurden und wie weit du selbst gehen kannst.<br>\r\n<br>\r\n<a href=\"https://forms.gle/ccrAC4MTpoEuBsqX8\"><strong>Anmeldung</strong></a><br>\r\n ",
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            "description": "<p>Eine App programmieren? Ein Computerspiel erfinden? Eine Animation gestalten?<br>\r\nWenn dich eines dieser Dinge interessiert, bist du hier am richtigen Ort! Tausche und teile deine Ideen, lerne zu programmieren und entdecke Informatikberufe.<br>\r\n<br>\r\nDie <a href=\"https://www.epfl.ch/education/education-and-science-outreach/de/jugendliche/coding-club/\">Coding Club for Girls</a> Workshops sind für Mädchen im Alter von 11 bis 15 Jahren und die Teilnahme ist kostenlos. Ab der Teilnahme an vier Workshops pro Jahr wird eine Teilnahmebestätigung ausgehändigt. <br>\r\n<br>\r\n<strong>Ort:</strong>  Kantonsschule, Zug<br>\r\n<br>\r\n<strong>Datum und Zeit:</strong><br>\r\n<strong>14. November 2026 : 09:30 bis 12:00  oder 13:30 bis 16:00 Uhr  // Schildkröte in Python<br>\r\n28. November 2026 : 09:30 bis 12:00 oder 13:30 bis 16:00 Uhr  // Mit Computern chatten</strong><br>\r\n<br>\r\nDie Inhalte der Workshops sind untenstehend beschrieben.<br>\r\n<br>\r\n<strong>Bedingungen</strong>\r\n</p><ul>\r\n\t<li>Gratis</li>\r\n\t<li><a href=\"https://forms.gle/WJT3oz5RCnWXZsQq6\">Anmeldung unter diesem Link </a></li>\r\n\t<li><a href=\"https://www.epfl.ch/education/education-and-science-outreach/de/teilnahmebedingungen/\">Allgemeine Teilnahmebedingungen EPFL - SPS Aktivitäten</a> </li>\r\n</ul>\r\n<strong>Workshops:</strong><br>\r\n<br>\r\n<strong>Schildkröte in Python - 14. November 2026</strong><br>\r\nLerne die Python-Programmiersprache kennen die in vielen Bereichen angewendet wird. Dank der “Turtle” die in Python zur Verfügung steht, verwandelt Codierlinien in schöne Zeichnungen und dir somit erlaubt diese Sprache zu verstehen.<br>\r\n<br>\r\n<strong>Mit Computern chatten - 28. November 2026</strong><br>\r\nComputer haben ihre eigene Sprache. Dank diesem Workshop wirst du lernen, mit einem Mikro-Computer zu kommunizieren, damit er macht, was du möchtest! Hilf uns einfache Programme zu debuggen und ein Spiel für zwei Spielerinnen zu entwerfen. <br>\r\n<br>\r\n<a href=\"https://forms.gle/WJT3oz5RCnWXZsQq6\"><strong>Anmeldung</strong></a><br>\r\n ",
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            "id": 71805,
            "title": "Coding Club for Girls in St. Gallen",
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            "description": "<p>Eine App programmieren? Ein Computerspiel erfinden? Eine Animation gestalten?<br>\r\nWenn dich eines dieser Dinge interessiert, bist du hier am richtigen Ort! Tausche und teile deine Ideen, lerne zu programmieren und entdecke Informatikberufe.<br>\r\n<br>\r\nDie <a href=\"https://www.epfl.ch/education/education-and-science-outreach/de/jugendliche/coding-club/\">Coding Club for Girls</a> Workshops sind für Mädchen im Alter von 11 bis 15 Jahren und die Teilnahme ist kostenlos. Ab der Teilnahme an vier Workshops pro Jahr wird eine Teilnahmebestätigung ausgehändigt. <br>\r\n<br>\r\n<strong>Ort:</strong>  Smartfeld, St. Gallen<br>\r\n<br>\r\n<strong>Datum und Zeit:</strong><br>\r\n<strong>Mittwoch, 18. November 2026: 13:30 bis 16:00 Uhr  // Hello 3D World</strong><br>\r\n<strong>Mittwoch, 25. November 2026 : 13:30 bis 16:00 Uhr  // Webdesignerin</strong><br>\r\n<br>\r\nDie Inhalte der Workshops sind untenstehend beschrieben.<br>\r\n<br>\r\n<strong>Bedingungen</strong>\r\n</p><ul>\r\n\t<li>Gratis</li>\r\n\t<li><a href=\"https://forms.gle/Bk4vieCLDPepMSL37\">Anmeldung unter diesem Link </a></li>\r\n\t<li><a href=\"https://www.epfl.ch/education/education-and-science-outreach/de/teilnahmebedingungen/\">Allgemeine Teilnahmebedingungen EPFL - SPS Aktivitäten</a> </li>\r\n</ul>\r\n<strong>Workshops:<br>\r\nHello 3D World - Mittwoch, 18. November 2026</strong><br>\r\nWie denkst du wurden die Figuren und Kulissen in den Filmen Shrek, Cars, Ice Age oder Kung Fu Panda gestaltet? Beim Entwerfen und Animieren von 3D-Objekten kannst Du wie im richtigen Animationsstudio gleichzeitig in die Rolle einer Künstlerin und einer Informatikerin schlüpfen. Du wirst dreidimensionale Objekte rund um das Thema Wald gestalten und in einem zweiten Schritt deiner Fantasie freien Lauf lassen und deine eigenen 3D-Objekte entwerfen!<br>\r\n<br>\r\n<strong>Webdesignerin - Mittwoch, 25. November 2026</strong><br>\r\nEntdecke den Hintergrund einer Webseite und entwerfe deine eigene von A bis Z mit derselben Sprache wie die Profis! An diesem Workshop wirst du mit HTML vertraut und wirst verstehen, wie Webseiten gestaltet wurden und wie weit du selbst gehen kannst.<br>\r\n<br>\r\n<a href=\"https://forms.gle/Bk4vieCLDPepMSL37\"><strong>Anmeldung</strong></a><br>\r\n ",
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        {
            "id": 71001,
            "title": "Gestion de projet européen - Projets ERC et MSCA",
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        {
            "id": 71686,
            "title": "Coding Club for Girls in Schaffhausen",
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            "lang": "en",
            "start_date": "2026-12-02",
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            "description": "<p>Eine App programmieren? Ein Computerspiel erfinden? Eine Animation gestalten?<br>\r\nWenn dich eines dieser Dinge interessiert, bist du hier am richtigen Ort! Tausche und teile deine Ideen, lerne zu programmieren und entdecke Informatikberufe. Die <a href=\"https://www.epfl.ch/education/education-and-science-outreach/de/jugendliche/coding-club/\">Coding Club for Girls</a> Workshops sind für Mädchen im Alter von 11 bis 15 Jahren.<br>\r\n<br>\r\nDie Workshops werden in Zusammenarbeit mit go tec! organisiert. Die Workshops können individuell besucht werden und die Teilnahme ist kostenlos.<br>\r\nAb der Teilnahme an vier Workshops pro Jahr wird eine Teilnahmebestätigung ausgehändigt. <br>\r\n <br>\r\n<strong>Ort:</strong>  go tec! Labor, Neuhausen am Rheinfall<br>\r\n<br>\r\n<strong>Datum und Zeit:</strong><br>\r\n<strong>02. Dezember 2026 : Mittwoch von 13:30 bis 16:00 Uhr  // Scratch-me<br>\r\n09. Dezember 2026</strong><strong> : Mittwoch von 13:30 bis 16:00 Uhr  // GameDesign</strong><br>\r\nDie Inhalte der Workshops sind untenstehend beschrieben.<br>\r\n<br>\r\n<strong>Scratch-me - Mittwoch,  02. Dezember 2026</strong><br>\r\nEinführung in die Programmierlogik mit der Konzeption von Animationen, Spielen und vieles mehr! Codieren ist wie eine neue Sprache lernen. Worte zu kennen bedeutet nicht unbedingt, die Sprache zu beherrschen. Man muss die Worte auch in der richtigen Reihenfolge platzieren können. Bei diesem Workshop lernt ihr Scratch, eine vereinfachte Programmiersprache, die sich in der Form von Blöcken präsentiert, die man richtig zusammenstellen muss.<br>\r\n<br>\r\n<br>\r\n<strong>GameDesign - Mittowch, 09. Dezember 2026</strong><br>\r\nErlebe neue Abenteuer mit unserem Lieblingskater! Egal ob du Anfängerin oder bereits Scratch-Expertin bist, es warten neuen Aufgaben auf dich! <br>\r\n<br>\r\n<br>\r\n<strong>Bedingungen</strong>\r\n</p><ul>\r\n\t<li>Gratis</li>\r\n\t<li><a href=\"https://forms.gle/MyxricscPXZugpmu5\">Anmeldung unter diesem Link </a></li>\r\n\t<li><a href=\"https://www.epfl.ch/education/education-and-science-outreach/de/teilnahmebedingungen/\">Allgemeine Teilnahmebedingungen EPFL - SPS Aktivitäten</a> </li>\r\n</ul>",
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