Event List
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GET /api/v1/events/?format=api&offset=120&ordering=-title
{ "count": 203, "next": "https://memento.epfl.ch/api/v1/events/?format=api&limit=10&offset=130&ordering=-title", "previous": "https://memento.epfl.ch/api/v1/events/?format=api&limit=10&offset=110&ordering=-title", "results": [ { "id": 70956, "title": "G protein-coupled receptors functional dynamics revealed by experimental and computational structural data", "slug": "g-protein-coupled-receptors-functional-dynamics-re", "event_url": "https://memento.epfl.ch/event/g-protein-coupled-receptors-functional-dynamics-re", "visual_url": "https://memento.epfl.ch/image/32345/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/32345/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/32345/max-size.jpg", "lang": "en", "start_date": "2026-10-07", "end_date": "2026-10-09", "start_time": null, "end_time": null, "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/g-protein-coupled-receptors-functional-dynamics-revealed-by-experimental-and-computational-structural-data-1488\">https://www.cecam.org/workshop-details/g-protein-coupled-receptors-functional-dynamics-revealed-by-experimental-and-computational-structural-data-1488</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\n<br>\r\nG protein-coupled receptors (GPCRs) represent a vast and diverse class of transmembrane proteins that orchestrate a wide range of physiological processes by responding to both endogenous and exogenous ligands [1,2]. These receptors are essential to critical functions such as metabolism, immune regulation, neuronal signaling, and sensory perception - including vision and olfaction. Due to their physiological relevance and membrane accessibility, GPCRs are the targets of approximately 34% of all prescribed medications, accounting for nearly 27% of the global pharmaceutical market [3]. <br>\r\nDespite their pharmaceutical importance, key aspects of GPCR function remain elusive. The canonical activation model posits that agonist binding to the extracellular orthosteric site triggers allosteric changes - most notably, the outward displacement of transmembrane helices 5 (TM5) and 6 (TM6) on the intracellular side - ultimately leading to receptor activation [2-4]. However, recent evidence suggests a more nuanced mechanism. In several GPCRs, activation appears to involve cooperative engagement between the agonist and the G protein. For example, the G protein may disrupt an \"inactivating ionic lock\" - a salt bridge between TM3 and TM6 - while the agonist stabilizes the active conformation. In some receptors, this is complemented by the formation of an “activating ionic lock” between TM5 and TM6 [5-8]. These dual contributions are considered thermodynamically essential for full activation [7].<br>\r\nAdding further complexity, GPCR activity is regulated by conformational microswitches and finely tuned intra-protein interaction networks. These dynamic rearrangements are difficult to capture and often elude direct correlation with functional outcomes. Moreover, allosteric ligands - which bind sites distinct from the orthosteric pocket - are being increasingly identified [9-12], along with small molecules capable of biased signaling, i.e., preferential activation of specific intracellular pathways [11-13, 16, 17]. These findings reveal a rich and underexplored conformational landscape that governs GPCR signaling. In addition, native membrane components—such as lipids and interacting proteins, including GPCR oligomers—are known to significantly modulate receptor function [11, 18-22].<br>\r\nTo disentangle these intricacies, computational modeling has become indispensable, offering atomistic insight into GPCR conformational dynamics and mechanistic understanding [1-2, 7, 11, 14, 16–21, 23]. Nevertheless, key questions remain - particularly regarding the structural basis of biased signaling, strategies for leveraging allosteric networks in pharmacology, and the modulatory role of the lipid environment. Addressing these gaps is crucial for both fundamental biology and the rational design of next-generation GPCR-targeting drugs with improved selectivity and safety profiles. <br>\r\nThese scientific challenges form the foundation of our upcoming workshop, which will focus on the latest experimental and computational approaches for studying the functional dynamics of GPCRs. Given the profound health, economic, and societal implications of modulating these receptors with precision, we aim to strengthen the interdisciplinary nature of the event by increasing the representation of experimental research and integrating cutting-edge artificial intelligence applications into the program.<br>\r\nBuilding upon the success of the 2022 and 2024 editions - which led to new collaborations and a landmark publication in <em>Nature Reviews Drug Discovery</em> [24] - our goal is to further enhance communication and collaboration between experimentalists and theoreticians. The workshop will serve as a reference point for young scientists and students, offering a platform to interact with leading international experts. We are confident that this initiative will foster insightful discussions and contribute meaningfully to advancing the field of GPCR pharmacology.<br>\r\n<br>\r\n<strong>References</strong><br>\r\n<br>\r\n<a href=\"https://doi.org/10.1038/nrd.2017.229\" target=\"_blank\">[1] J. Smith, R. Lefkowitz, S. Rajagopal, Nat. Rev. Drug. Discov., <strong>17</strong>, 243-260 (2018)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41573-024-01083-3\" target=\"_blank\">[2] P. Conflitti, E. Lyman, M. Sansom, P. Hildebrand, H. Gutiérrez-de-Terán, P. Carloni, T. Ansell, S. Yuan, P. Barth, A. Robinson, C. Tate, D. Gloriam, S. Grzesiek, M. Eddy, S. Prosser, V. Limongelli, Nat. Rev. Drug. Discov., <strong>24</strong>, 251-275 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41589-024-01682-6\" target=\"_blank\">[3] L. Picard, A. Orazietti, D. Tran, A. Tucs, S. Hagimoto, Z. Qi, S. Huang, K. Tsuda, A. Kitao, A. Sljoka, R. Prosser, Nat. Chem. Biol., <strong>21</strong>, 71-79 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.drudis.2020.10.006\" target=\"_blank\">[4] B. Huang, C. St. Onge, H. Ma, Y. Zhang, Drug Discovery Today, <strong>26</strong>, 189-199 (2021)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41467-023-42082-z\" target=\"_blank\">[5] D. Di Marino, P. Conflitti, S. Motta, V. Limongelli, Nat. Commun., <strong>14</strong>, 6439 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.ceb.2018.10.007\" target=\"_blank\">[6] G. Milligan, R. Ward, S. Marsango, Current Opinion in Cell Biology, <strong>57</strong>, 40-47 (2019)</a><br>\r\n<a href=\"https://doi.org/10.7554/elife.73901\" target=\"_blank\">[7] S. Huang, O. Almurad, R. Pejana, Z. Morrison, A. Pandey, L. Picard, M. Nitz, A. Sljoka, R. Prosser, eLife, <strong>11</strong>, (2022)</a><br>\r\n<a href=\"https://doi.org/10.1146/annurev-pharmtox-010919-023411\" target=\"_blank\">[8] A. Duncan, W. Song, M. Sansom, Annu. Rev. Pharmacol. Toxicol., <strong>60</strong>, 31-50 (2020)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41467-025-60003-0\" target=\"_blank\">[9] A. Morales-Pastor, T. Miljuš, M. Dieguez-Eceolaza, T. Stępniewski, V. Ledesma-Martin, F. Heydenreich, T. Flock, B. Plouffe, C. Le Gouill, J. Duchaine, D. Sykes, C. Nicholson, E. Koers, W. Guba, A. Rufer, U. Grether, M. Bouvier, D. Veprintsev, J. Selent, Nat. Commun., <strong>16</strong>, 5265 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41586-022-05588-y\" target=\"_blank\">[10] A. Faouzi, H. Wang, S. Zaidi, J. DiBerto, T. Che, Q. Qu, M. Robertson, M. Madasu, A. El Daibani, B. Varga, T. Zhang, C. Ruiz, S. Liu, J. Xu, K. Appourchaux, S. Slocum, S. Eans, M. Cameron, R. Al-Hasani, Y. Pan, B. Roth, J. McLaughlin, G. Skiniotis, V. Katritch, B. Kobilka, S. Majumdar, Nature, <strong>613</strong>, 767-774 (2022)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41467-022-31652-2\" target=\"_blank\">[11] M. Wall, E. Hill, R. Huckstepp, K. Barkan, G. Deganutti, M. Leuenberger, B. Preti, I. Winfield, S. Carvalho, A. Suchankova, H. Wei, D. Safitri, X. Huang, W. Imlach, C. La Mache, E. Dean, C. Hume, S. Hayward, J. Oliver, F. Zhao, D. Spanswick, C. Reynolds, M. Lochner, G. Ladds, B. Frenguelli, Nat. Commun., <strong>13</strong>, 4150 (2022)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41580-018-0049-3\" target=\"_blank\">[12] D. Wootten, A. Christopoulos, M. Marti-Solano, M. Babu, P. Sexton, Nat. Rev. Mol. Cell. Biol., <strong>19</strong>, 638-653 (2018)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41594-017-0011-7\" target=\"_blank\">[13] D. Hilger, M. Masureel, B. Kobilka, Nat. Struct. Mol. Biol., <strong>25</strong>, 4-12 (2018)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41467-025-57034-y\" target=\"_blank\">[14] D. Aranda-García, T. Stepniewski, M. Torrens-Fontanals, A. García-Recio, M. Lopez-Balastegui, B. Medel-Lacruz, A. Morales-Pastor, A. Peralta-García, M. Dieguez-Eceolaza, D. Sotillo-Nuñez, T. Ding, M. Drabek, C. Jacquemard, J. Jakowiecki, W. Jespers, M. Jiménez-Rosés, V. Jun-Yu-Lim, A. Nicoli, U. Orzel, A. Shahraki, J. Tiemann, V. Ledesma-Martin, F. Nerín-Fonz, S. Suárez-Dou, O. Canal, G. Pándy-Szekeres, J. Mao, D. Gloriam, E. Kellenberger, D. Latek, R. Guixà-González, H. Gutiérrez-de-Terán, I. Tikhonova, P. Hildebrand, M. Filizola, M. Babu, A. Di Pizio, S. Filipek, P. Kolb, A. Cordomi, T. Giorgino, M. Marti-Solano, J. Selent, Nat. Commun., <strong>16</strong>, 2020 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41586-018-0259-z\" target=\"_blank\">[15] D. Thal, A. Glukhova, P. Sexton, A. Christopoulos, Nature, <strong>559</strong>, 45-53 (2018)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.tips.2020.12.005\" target=\"_blank\">[16] L. Slosky, M. Caron, L. Barak, Trends in Pharmacological Sciences, <strong>42</strong>, 283-299 (2021)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.apsb.2023.07.020\" target=\"_blank\">[17] C. Zhu, X. Lan, Z. Wei, J. Yu, J. Zhang, Acta Pharmaceutica Sinica B, <strong>14</strong>, 67-86 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.chempr.2024.08.004\" target=\"_blank\">[18] V. D’Amore, P. Conflitti, L. Marinelli, V. Limongelli, Chem, <strong>10</strong>, 3678-3698 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41557-023-01238-6\" target=\"_blank\">[19] A. Mafi, S. Kim, W. Goddard, Nat. Chem., <strong>15</strong>, 1127-1137 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41594-024-01334-2\" target=\"_blank\">[20] H. Batebi, G. Pérez-Hernández, S. Rahman, B. Lan, A. Kamprad, M. Shi, D. Speck, J. Tiemann, R. Guixà-González, F. Reinhardt, P. Stadler, M. Papasergi-Scott, G. Skiniotis, P. Scheerer, B. Kobilka, J. Mathiesen, X. Liu, P. Hildebrand, Nat. Struct. Mol. Biol., <strong>31</strong>, 1692-1701 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.cell.2015.04.043\" target=\"_blank\">[21] A. Manglik, T. Kim, M. Masureel, C. Altenbach, Z. Yang, D. Hilger, M. Lerch, T. Kobilka, F. Thian, W. Hubbell, R. Prosser, B. Kobilka, Cell, <strong>161</strong>, 1101-1111 (2015)</a><br>\r\n<a href=\"https://doi.org/10.1016/j.cell.2020.03.003\" target=\"_blank\">[22] M. Congreve, C. de Graaf, N. Swain, C. Tate, Cell, <strong>181</strong>, 81-91 (2020)</a><br>\r\n<a href=\"https://doi.org/10.1038/s41573-025-01139-y\" target=\"_blank\">[23] J. Lorente, A. Sokolov, G. Ferguson, H. Schiöth, A. Hauser, D. Gloriam, Nat. Rev. Drug. Discov., <strong>24</strong>, 458-479 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1111/bph.16495\" target=\"_blank\">[24] M. Lopez‐Balastegui, T. Stepniewski, M. Kogut‐Günthel, A. Di Pizio, M. Rosenkilde, J. Mao, J. Selent, British. J. Pharmacology., <strong>182</strong>, 3211-3224 (2024)</a>\r\n</p><div class=\"active tab-pane\"> </div>", "image_description": "", "creation_date": "2026-01-26T16:00:31", "last_modification_date": "2026-01-26T16:45:08", "link_label": "G protein-coupled receptors functional dynamics revealed by experimental and computational structura", "link_url": "https://www.cecam.org/workshop-details/g-protein-coupled-receptors-functional-dynamics-revealed-by-experimental-and-computational-structural-data-1488", "canceled": "False", "cancel_reason": "", "place_and_room": "Aula Magna, USI Lugano", "url_place_and_room": "https://www.desk.usi.ch/en/lugano-campus-map-access-facilities", "url_online_room": "", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "", "organizer": "<strong>Vittorio Limongelli</strong>, Università della Svizzera Italiana USI Lugano ; <strong>Scott Prosser</strong>, University of Toronto ; <strong>Stefano Raniolo</strong>, Università della Svizzera Italiana ; <strong>Jana Selent</strong>, Hospital Del Mar Medical Research Institute", "contact": "<a href=\"mailto:[email protected]\"><strong>Cornelia Bujenita</strong></a>, CECAM Events and Operations Manager", "is_internal": "False", "theme": "", "vulgarization": { "id": 2, "fr_label": "Public averti", "en_label": "Informed public" }, "registration": { "id": 1, "fr_label": "Sur inscription", "en_label": "Registration required" }, "keywords": "", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/119453/", "category": { "id": 1, "code": "CONF", "fr_label": "Conférences - Séminaires", "en_label": "Conferences - Seminars", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/1/?format=api", "https://memento.epfl.ch/api/v1/mementos/5/?format=api", "https://memento.epfl.ch/api/v1/mementos/6/?format=api", "https://memento.epfl.ch/api/v1/mementos/8/?format=api", "https://memento.epfl.ch/api/v1/mementos/27/?format=api" ] }, { "id": 71934, "title": "Future of Health Grant", "slug": "future-of-health-grant-3", "event_url": "https://memento.epfl.ch/event/future-of-health-grant-3", "visual_url": "https://memento.epfl.ch/image/33245/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/33245/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/33245/max-size.jpg", "lang": "en", "start_date": "2026-07-31", "end_date": "2026-07-31", "start_time": "11:00:00", "end_time": "12:00:00", "description": "<p>The <strong>Future of Health Grant</strong> is a support program dedicated to accelerating early‑stage digital health startups developing solutions relevant to the Swiss healthcare system.<br>\r\nCreated by CSS and the EPFL Innovation Park, it combines equity‑free funding, expert guidance and access to healthcare stakeholders to help founders progress from prototype to real‑world validation.<br>\r\n<br>\r\n<strong>For whom</strong>\r\n</p><ul>\r\n\t<li>For early‑stage digital health startups developing solutions that can be applied within the Swiss healthcare system.</li>\r\n\t<li>Eligible teams may be based in Switzerland or abroad, provided their innovation is relevant to Swiss clinical, operational or preventive care contexts.</li>\r\n\t<li>The program targets founders at the prototype, MVP or early validation stage.</li>\r\n</ul>\r\n<strong>What you gain</strong>\r\n\r\n<ul>\r\n\t<li><strong>equity‑free financial support</strong> at three possible levels (CHF 10k, 30k or 50k), depending on project maturity and needs</li>\r\n\t<li>teams benefit from <strong>structured coaching</strong>, <strong>industry mentoring</strong></li>\r\n\t<li>access to <strong>paid specialists</strong> through the “CxO as a Service” model</li>\r\n\t<li>The program also facilitates <strong>real‑world validation</strong> opportunities with healthcare professionals, hospitals, insurers and ecosystem partners in Switzerland</li>\r\n</ul>\r\n<strong>How it works</strong><br>\r\n<br>\r\nThe program operates fully virtually and follows a milestone‑based approach. Selected startups receive regular guidance from experts in digital health, business development and regulatory pathways. Each team works toward defined objectives, with progress reviewed at set intervals. The program supports founders in strengthening their product, business model and clinical relevance.<br>\r\n<strong>Program context</strong><br>\r\n<br>\r\nLaunched in 2022, the Future of Health Grant is an initiative of <strong>CSS</strong> and the <strong>EPFL Innovation Park</strong>. Its mission is to accelerate the adoption of impactful digital health solutions by bridging early‑stage innovation with the needs of real healthcare systems.", "image_description": "", "creation_date": "2026-05-22T13:39:38", "last_modification_date": "2026-05-22T13:39:44", "link_label": "Webpage", "link_url": "https://future-of-health.org/", "canceled": "False", "cancel_reason": "", "place_and_room": "", "url_place_and_room": "", "url_online_room": "", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "", "organizer": "<a href=\"https://future-of-health.org/\">Future of Health Grant</a>, a programm powered by Fondation EPFL Innovation Park", "contact": "Mathilde Durvy <a href=\"mailto:[email protected]\">[email protected]</a>", "is_internal": "False", "theme": "", "vulgarization": { "id": 2, "fr_label": "Public averti", "en_label": "Informed public" }, "registration": { "id": 1, "fr_label": "Sur inscription", "en_label": "Registration required" }, "keywords": "", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/120842/", "category": { "id": 17, "code": "DEADLINE", "fr_label": "Echéance", "en_label": "Deadline", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/422/?format=api" ] }, { "id": 71751, "title": "From Exploitation to Mitigation: Analyzing Memory Corruption Primitives to Harden the Linux Kernel", "slug": "from-exploitation-to-mitigation-analyzing-memory-c", "event_url": "https://memento.epfl.ch/event/from-exploitation-to-mitigation-analyzing-memory-c", "visual_url": "https://memento.epfl.ch/image/33078/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/33078/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/33078/max-size.jpg", "lang": "en", "start_date": "2026-06-23", "end_date": "2026-06-23", "start_time": "10:00:00", "end_time": "12:00:00", "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. George Candea<br>\r\nThesis advisor: Prof. Mathias Payer<br>\r\nThesis co-advisor: Dr. Anil Kurmus<br>\r\nCo-examiner: Prof. Sanidhya Kashyap<br>\r\n<br>\r\n<u>Abstract</u><br>\r\ncoming soon<br>\r\n<br>\r\n<u>Selected papers</u><br>\r\ncoming soon", "image_description": "", "creation_date": "2026-04-29T09:44:15", "last_modification_date": "2026-04-29T09:44:15", "link_label": "", "link_url": "", "canceled": "False", "cancel_reason": "", "place_and_room": "BC 133", "url_place_and_room": "https://plan.epfl.ch/?room==BC%20133", "url_online_room": "", "spoken_languages": [], "speaker": "Claudio Migliorelli", "organizer": "", "contact": "[email protected]", "is_internal": "False", "theme": "", "vulgarization": { "id": 1, "fr_label": "Tout public", "en_label": "General public" }, "registration": { "id": 3, "fr_label": "Entrée libre", "en_label": "Free" }, "keywords": "EDIC candidacy exam", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/120583/", "category": { "id": 1, "code": "CONF", "fr_label": "Conférences - Séminaires", "en_label": "Conferences - Seminars", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/6/?format=api", "https://memento.epfl.ch/api/v1/mementos/27/?format=api", "https://memento.epfl.ch/api/v1/mementos/48/?format=api" ] }, { "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", "visual_url": "https://memento.epfl.ch/image/32346/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/32346/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/32346/max-size.jpg", "lang": "en", "start_date": "2026-10-14", "end_date": "2026-10-16", "start_time": null, "end_time": null, "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>", "image_description": "", "creation_date": "2026-01-26T16:07:22", "last_modification_date": "2026-01-26T16:45:31", "link_label": "From Data to Dynamics: Machine Learning in Statistical Mechanics and Molecular Simulations", "link_url": "https://www.cecam.org/workshop-details/from-data-to-dynamics-machine-learning-in-statistical-mechanics-and-molecular-simulations-1487", "canceled": "False", "cancel_reason": "", "place_and_room": "Aula Magna, USI Lugano", "url_place_and_room": "https://www.desk.usi.ch/en/lugano-campus-map-access-facilities", "url_online_room": "", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "", "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", "is_internal": "False", "theme": "", "vulgarization": { "id": 2, "fr_label": "Public averti", "en_label": "Informed public" }, "registration": { "id": 1, "fr_label": "Sur inscription", "en_label": "Registration required" }, "keywords": "", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/119454/", "category": { "id": 1, "code": "CONF", "fr_label": "Conférences - Séminaires", "en_label": "Conferences - Seminars", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/1/?format=api", "https://memento.epfl.ch/api/v1/mementos/5/?format=api", "https://memento.epfl.ch/api/v1/mementos/6/?format=api", "https://memento.epfl.ch/api/v1/mementos/8/?format=api", "https://memento.epfl.ch/api/v1/mementos/27/?format=api" ] }, { "id": 61304, "title": "FondAction contre le Cancer | Grants for applied cancer research", "slug": "fondaction-contre-le-cancer-grants-for-applied-c-7", "event_url": "https://memento.epfl.ch/event/fondaction-contre-le-cancer-grants-for-applied-c-7", "visual_url": "https://memento.epfl.ch/image/23395/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/23395/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/23395/max-size.jpg", "lang": "en", "start_date": "2026-09-15", "end_date": "2026-09-15", "start_time": null, "end_time": null, "description": "<p>Established in Lausanne in 1999, <strong>FondAction contre le Cancer</strong> supports <strong>applied cancer research</strong> for the <strong>benefit of patients</strong>, particularly in <strong>Switzerland</strong>. The foundation offers 2 funding instruments:<br>\r\n<br>\r\n<strong>GRANTS </strong>\r\n</p><ul>\r\n\t<li><strong>What:</strong> For collaborative applied research projects related to cancer. The research topic can be preclinical, translational, clinical or of public health. A priority will be given to projects involving the development of innovative therapies for patients. Preclinical research should not be basic research but should be as close<br>\r\n\tto the clinic as possible.</li>\r\n\t<li><strong>Who can apply:</strong> team of applicants. The main applicant (MD, PhD, nurse or else) must be <strong>Swiss or be employed by a Swiss institution</strong> and should demonstrate the ability to lead and finalize an innovative research project.</li>\r\n\t<li><strong>Funding</strong>: no upper or lower limit. The grant does NOT cover the main applicant’s salary. You must have and mention other sources of funding.</li>\r\n\t<li><strong>Duration:</strong> max 36 months.</li>\r\n\t<li>More details <a href=\"https://www.fondaction.ch/wp-content/uploads/2025/04/Grant-Request-conditions-and-rules_2025.pdf\">here</a></li>\r\n</ul>\r\n<br>\r\n<strong>YOUNG INVESTIGATOR GRANTS</strong>\r\n\r\n<ul>\r\n\t<li><strong>What:</strong> Support to young researchers in the field of oncology <strong>in</strong> <strong>Switzerland</strong>, to help them at the beginning of their academic career. The research topic can be pre-clinical or clinical or of public health.</li>\r\n\t<li><strong>Who can apply:</strong> the young investigator must be an MD, a PhD in biology or health care, be <strong>Swiss or be employed by a Swiss institution</strong>, < 40 year old, have the support of his/her supervisor and the opportunity to build a career at the institution of employment.</li>\r\n\t<li><strong>Funding: </strong>CHF 100’000. The grant does NOT cover the main applicant’s salary.</li>\r\n\t<li><strong>Duration:</strong> 24 months.</li>\r\n\t<li>More details <a href=\"https://www.fondaction.ch/wp-content/uploads/2025/04/YIA-conditions-and-rules_2025.pdf\">here</a></li>\r\n</ul>\r\n<strong>Deadline: 15 September 2026</strong><br>\r\n<br>\r\nProposals are evaluated by the foundation’s <a href=\"https://www.fondaction.ch/fondation/conseil-de-fondation/\">scientific committee</a> and external experts.<br>\r\n<br>\r\n<strong>For more information</strong>, please have a look at the <a href=\"https://www.fondaction.ch/\">call webpage + supported projects</a><u>.</u><br>\r\n ", "image_description": "", "creation_date": "2022-12-16T18:09:01", "last_modification_date": "2026-05-18T15:30:33", "link_label": "", "link_url": "", "canceled": "False", "cancel_reason": "", "place_and_room": "", "url_place_and_room": "", "url_online_room": "", "spoken_languages": [], "speaker": "", "organizer": "", "contact": "<a href=\"mailto:[email protected]?subject=%5B%20FondAction%20contre%20le%20Cancer%20%7C%20Grants%20for%20applied%20cancer%20research%20%5D\">Research Office</a>", "is_internal": "False", "theme": "", "vulgarization": { "id": 1, "fr_label": "Tout public", "en_label": "General public" }, "registration": { "id": 3, "fr_label": "Entrée libre", "en_label": "Free" }, "keywords": "", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/105284/", "category": { "id": 16, "code": "PROP", "fr_label": "Appel à proposition", "en_label": "Call for proposal", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/140/?format=api" ] }, { "id": 71787, "title": "First Swiss Ultra High Field MRI Symposium", "slug": "first-swiss-ultra-high-field-mri-symposium", "event_url": "https://memento.epfl.ch/event/first-swiss-ultra-high-field-mri-symposium", "visual_url": "https://memento.epfl.ch/image/33110/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/33110/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/33110/max-size.jpg", "lang": "en", "start_date": "2026-06-03", "end_date": "2026-06-03", "start_time": "09:00:00", "end_time": "17:30:00", "description": "<p>Ultra-high-field MRI is delivering tangible clinical impact. With four 7T systems nationwide, Switzerland is uniquely positioned to drive efficient translational innovation in advanced imaging. This first national UHF MRI symposium brings together the experts shaping the future of UHF MRI in Switzerland and beyond. The event aims to address unmet clinical needs, spark new collaborative projects, and strengthen a community dedicated to advancing patient care through innovation. The CIBM is proud to be one of the organizers of the event, which will take place at the Sitem-insel on in Bern on June 3, 2026.\r\n</p><div class=\"animated animated-slow e-con e-con-full e-flex e-lazyloaded e-parent elementor-element elementor-element-72ea616 fadeInRight\">\r\n<div class=\"e-child e-con e-con-boxed e-flex elementor-element elementor-element-c597026\">\r\n<div class=\"e-con-inner\">\r\n<div class=\"e-child e-con e-con-full e-flex elementor-element elementor-element-24db839\">\r\n<div class=\"elementor-element elementor-element-6792407 elementor-widget elementor-widget-text-editor\">\r\n<div class=\"elementor-widget-container\">\r\n<div class=\"Vq6kJx Z_l5lU comp-mhnlzx65 ku3DBC qvSjx3 wixui-rich-text zQ9jDz\"><strong>Audience</strong>\r\n<ul>\r\n\t<li>Clinical and scientific leaders in (UHF) MRI.</li>\r\n\t<li>Translational researchers in neuro, MSK, body, cardiac, and oncology.</li>\r\n\t<li>MR physicists, RF engineers, and AI/reconstruction innovators.</li>\r\n\t<li>Industry and strategic partners across hardware, software, safety, and services.</li>\r\n</ul>\r\n<strong>Program Highlights</strong>\r\n\r\n<ul>\r\n\t<li>Keynotes & panels: advancing UHF MRI toward clinical value (safety, SAR, regulation, harmonization).</li>\r\n\t<li>Challenge session: unmet clinical needs and solution pitches.</li>\r\n\t<li>Strategies for new collaborative projects.</li>\r\n\t<li>Building a community driving patient impact through innovation and synergy.</li>\r\n</ul>\r\n</div>\r\n</div>\r\n</div>\r\n</div>\r\n</div>\r\n</div>\r\n</div>", "image_description": "First Swiss Ultra High Field MRI Symposium", "creation_date": "2026-05-04T13:18:36", "last_modification_date": "2026-05-04T13:21:21", "link_label": "Website of the event", "link_url": "https://swiss-uhf-mri.cibm.ch/", "canceled": "False", "cancel_reason": "", "place_and_room": "", "url_place_and_room": "", "url_online_room": "", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "", "organizer": "", "contact": "Miguel Molina", "is_internal": "False", "theme": "", "vulgarization": { "id": 1, "fr_label": "Tout public", "en_label": "General public" }, "registration": { "id": 3, "fr_label": "Entrée libre", "en_label": "Free" }, "keywords": "7T MRI scanner, fMRI, UHF, Biomedical imaging", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/120632/", "category": { "id": 1, "code": "CONF", "fr_label": "Conférences - Séminaires", "en_label": "Conferences - Seminars", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/1/?format=api", "https://memento.epfl.ch/api/v1/mementos/5/?format=api", "https://memento.epfl.ch/api/v1/mementos/6/?format=api", "https://memento.epfl.ch/api/v1/mementos/8/?format=api", "https://memento.epfl.ch/api/v1/mementos/9/?format=api", "https://memento.epfl.ch/api/v1/mementos/284/?format=api" ] }, { "id": 71932, "title": "Failure-Aware LLM Serving for Agentic Workloads", "slug": "failure-aware-llm-serving-for-agentic-workloads", "event_url": "https://memento.epfl.ch/event/failure-aware-llm-serving-for-agentic-workloads", "visual_url": null, "visual_large_url": null, "visual_maxsize_url": null, "lang": "en", "start_date": "2026-06-17", "end_date": "2026-06-17", "start_time": "09:00:00", "end_time": "11:00:00", "description": "<u>EDIC candidacy exam</u><br>\r\nExam president: Prof. Anastasia Ailamaki<br>\r\nThesis advisor: Prof. Anne-Marie Kermarrec<br>\r\nCo-examiner: Prof. Robert West<br>\r\n<br>\r\n<u>Abstract</u><br>\r\n<br>\r\n<br>\r\n<u>Selected papers</u>\r\n<ul>\r\n\t<li>ReAct (<a href=\"https://arxiv.org/pdf/2210.03629\" target=\"_blank\">https://arxiv.org/pdf/2210.03629</a>)</li>\r\n\t<li>Agentix (<a href=\"https://www.usenix.org/system/files/nsdi26-luo.pdf\" target=\"_blank\">https://www.usenix.org/system/files/nsdi26-luo.pdf</a>)</li>\r\n\t<li>Why do multi-agent systems fail? (<a href=\"https://arxiv.org/pdf/2503.13657\" target=\"_blank\">https://arxiv.org/pdf/2503.13657</a>)</li>\r\n</ul>", "image_description": "", "creation_date": "2026-05-22T13:11:09", "last_modification_date": "2026-05-22T13:12:05", "link_label": "", "link_url": "", "canceled": "False", "cancel_reason": "", "place_and_room": "BC 133", "url_place_and_room": "https://plan.epfl.ch/?room==BC%20133", "url_online_room": "", "spoken_languages": [], "speaker": "Palak", "organizer": "", "contact": "[email protected]", "is_internal": "False", "theme": "", "vulgarization": { "id": 1, "fr_label": "Tout public", "en_label": "General public" }, "registration": { "id": 3, "fr_label": "Entrée libre", "en_label": "Free" }, "keywords": "EDIC candidacy exam", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/120839/", "category": { "id": 1, "code": "CONF", "fr_label": "Conférences - Séminaires", "en_label": "Conferences - Seminars", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/48/?format=api", "https://memento.epfl.ch/api/v1/mementos/6/?format=api", "https://memento.epfl.ch/api/v1/mementos/27/?format=api" ] }, { "id": 71759, "title": "Exploring new dimensions of the DNA damage response", "slug": "exploring-new-dimensions-of-the-dna-damage-respons", "event_url": "https://memento.epfl.ch/event/exploring-new-dimensions-of-the-dna-damage-respons", "visual_url": "https://memento.epfl.ch/image/33086/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/33086/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/33086/max-size.jpg", "lang": "en", "start_date": "2026-05-28", "end_date": "2026-05-28", "start_time": "09:00:00", "end_time": "09:45:00", "description": "<p>The ELISIR program recruits exceptional young talents directly after their Ph.D. to run a small team of scientists pursuing innovative independent research in the Life Sciences.<br>\r\nFeel free to attend this presentation (in SV 1717 or virtually via the zoom link) !<br>\r\n </p>", "image_description": "", "creation_date": "2026-04-29T16:37:08", "last_modification_date": "2026-04-30T14:39:36", "link_label": "", "link_url": "", "canceled": "False", "cancel_reason": "", "place_and_room": "SV 1717", "url_place_and_room": "https://plan.epfl.ch/?room=%3DSV%201717&dim_floor=1&lang=fr&dim_lang=fr&tree_groups=centres_nevralgiques_grp%2Cmobilite_acces_grp%2Crestauration_et_commerces_grp%2Censeignement%2Cservices_campus_grp%2Cequipements_grp&tree_group_layers_centres_nevralgiques_grp=&tree_group_layers_mobilite_acces_grp=metro&tree_group_layers_restauration_et_commerces_grp=&tree_group_layers_enseignement=guichet_etudiants&tree_group_layers_services_campus_grp=information_epfl&tree_group_layers_equipements_grp=&baselayer_ref=grp_backgrounds&map_x=2532836&map_y=1152453&map_zoom=14", "url_online_room": "https://epfl.zoom.us/j/68896362044", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "Sarah Moser, Netherlands Cancer Institute (NKI)", "organizer": "Pierre Gönczy, ELISIR program committee ", "contact": "Pierre Gönczy", "is_internal": "False", "theme": "", "vulgarization": { "id": 1, "fr_label": "Tout public", "en_label": "General public" }, "registration": { "id": 3, "fr_label": "Entrée libre", "en_label": "Free" }, "keywords": "Elisir sarah moser gönczy", "file": "https://memento.epfl.ch/public/upload/files/Slide1.JPG", "icalendar_url": "https://memento.epfl.ch/event/export/120593/", "category": { "id": 1, "code": "CONF", "fr_label": "Conférences - Séminaires", "en_label": "Conferences - Seminars", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/1/?format=api", "https://memento.epfl.ch/api/v1/mementos/6/?format=api", "https://memento.epfl.ch/api/v1/mementos/8/?format=api", "https://memento.epfl.ch/api/v1/mementos/9/?format=api", "https://memento.epfl.ch/api/v1/mementos/27/?format=api" ] }, { "id": 71885, "title": "Eveline Mayner's Public Defense", "slug": "eveline-mayner-s-public-defense", "event_url": "https://memento.epfl.ch/event/eveline-mayner-s-public-defense", "visual_url": null, "visual_large_url": null, "visual_maxsize_url": null, "lang": "en", "start_date": "2026-05-29", "end_date": "2026-05-29", "start_time": "04:00:00", "end_time": "22:00:00", "description": "<p>Two-dimensional (2D) materials have emerged as a versatile platform at the intersection of fundamental physics and applied science. Their atomically thin nature gives rise to distinctive electronic and optical properties, while simultaneously enabling them to function as highly sensitive, readily integrable probes of their local environment. Advanced optical techniques, such as super-resolution microscopy, have opened new opportunities to interrogate these materials at the nanoscale, providing optical access to individual defect behaviors, exciton diffusion and recombination dynamics, and charge transport pathways. Such approaches not only deepen our understanding of intrinsic material behavior but also position 2D systems as powerful sensors capable of resolving local dielectric variations, electric and magnetic fields, and other environmental perturbations.<br>\r\nCentral to this work is hexagonal boron nitride (hBN), a transparent, wide bandgap semiconductor that serves as a host for optically active defects. These defects function as reaction centers, single-photon emitters, and spatially resolved nanoscale sensors that can be readily integrated into electronic and photonic architectures. Owing to its optical transparency, chemical stability, and compatibility with diverse material platforms, hBN provides an exceptional foundation for optical sensing. Building upon this foundation, we explore material properties and present new methods for spatially resolved in situ optical imaging with hBN to advance dynamic, wide-field optical sensing.<br>\r\nWe investigate a previously reported class of emitters that arise from interactions between native hBN and organic solvents. These emitters are believed to originate from defect sites that bind transiently to solvent molecules. To study their behavior, we develop a platform for imaging the dynamics of these transient emitters while varying the electrochemical potential and applying electric fields with controlled orientations. By tracking the spectra of individual emitters, we enable multiplexed measurements that allow spatially resolved electrochemical imaging. Through systematic analysis, we rule out modulation mechanisms based on direct electric field effects or charge transfer. Instead, we identify a mechanism driven by changes in H⁺ concentration, which is modulated during the oxidation of trace water present in the solvent. This finding opens the possibility of using this platform for sensitive detection of H⁺ and trace water in methanol fuel cells, where such species critically influence operational efficiency.<br>\r\nIn the final part of the thesis, we focus on a well-characterized spin defect in hBN, the negatively charged boron vacancy, and explore strategies to enhance its photoluminescence (PL) through heterostructure engineering that facilitates energy and exciton transfer. We demonstrate the coupled structure’s improved utility in optical magnetometry compared to the defect by itself and discuss how improvements in PL could advance the development of wide-field optically detected magnetic resonance (ODMR) imaging using this spin defect. Using a defect in hBN would leverage 2D materials’ exceptional sensing capabilities and planar integrability.<br>\r\nOverall, this thesis aims to highlight the strengths of integrating 2D materials with optical sensing and to develop transferable techniques for introducing controlled stimuli, such as electrochemical potentials, electric fields, or electromagnetic waves, with high fidelity and minimal artifacts. These advances not only demonstrate the potential of hBN as a versatile sensing platform but also establish methodologies applicable to a wide range of low-dimensional material systems.<br>\r\n<br>\r\nFor zoom:<br>\r\n Meeting ID: 611 3428 2068 Passcode: 952027</p>", "image_description": "", "creation_date": "2026-05-13T16:07:39", "last_modification_date": "2026-05-13T16:07:39", "link_label": "", "link_url": "", "canceled": "False", "cancel_reason": "", "place_and_room": "ELA 1", "url_place_and_room": "https://plan.epfl.ch/?room==ELA%201", "url_online_room": "https://epfl.zoom.us/j/61134282068?pwd=zurg0qXVsUx4ln0hxCcrvjDCiHhwSx.1", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "Eveline Mayner\r\n\r\nAleksandra Radenovic", "organizer": "Eveline Mayner", "contact": "[email protected]", "is_internal": "False", "theme": "", "vulgarization": { "id": 1, "fr_label": "Tout public", "en_label": "General public" }, "registration": { "id": 3, "fr_label": "Entrée libre", "en_label": "Free" }, "keywords": "Public Defense", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/120775/", "category": { "id": 4, "code": "DIVERS", "fr_label": "Autres types d’événement", "en_label": "Miscellaneous", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/8/?format=api" ] }, { "id": 68778, "title": "ERC Synergy Grants", "slug": "erc-synergy-grants", "event_url": "https://memento.epfl.ch/event/erc-synergy-grants", "visual_url": "https://memento.epfl.ch/image/30331/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/30331/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/30331/max-size.jpg", "lang": "en", "start_date": "2026-11-05", "end_date": "2026-11-05", "start_time": null, "end_time": null, "description": "<strong>Call closed<br>\r\n<br>\r\nAim</strong><br>\r\nFor a group of <strong>two to maximum four Principal Investigators (PIs) </strong>working together and bringing different skills and resources to tackle ambitious research problems. One will be designated as the corresponding PI (cPI). The synergistic element to solve important research challenges is the key element for successful project proposals.<br>\r\n<br>\r\n<strong>Funding</strong><br>\r\nMax. EUR 10 Mio for a period of max. 6 years (including 25% overhead; pro rata temporis for shorter project duration). However, an additional EUR 4 million can be made available to cover eligible “start-up” costs for researchers moving from a third country to the EU or an associated country and/or the purchase of major equipment and/or access to large facilities and/or other major experimental and field work costs, including personnel costs.<br>\r\n<br>\r\n<strong>Eligibility</strong><br>\r\nNo specific eligibility criteria regarding the academic training are foreseen for ERC Synergy Grants. PIs must present a competitive<strong> </strong>track record as appropriate to their career stage.<br>\r\n<br>\r\n<strong>Deadline for proposal submissions</strong><br>\r\nTBC<br>\r\nProposals are submitted via the <a href=\"https://ec.europa.eu/info/funding-tenders/opportunities/portal/screen/opportunities/calls-for-proposals?isExactMatch=true&status=31094501,31094502,31094503&order=DESC&pageNumber=1&pageSize=50&sortBy=startDate\">EU Funding & Tenders portal</a><br>\r\n<br>\r\n<strong>Support and information</strong>\r\n<ul>\r\n\t<li>EPFL toolkit , with budget calculator and useful information for the proposal preparation will be provided upon call opening.</li>\r\n\t<li>For proposal writing services and administrative assistance with the proposal preparation please contact <a href=\"mailto:[email protected]\">[email protected]</a>.</li>\r\n\t<li><a href=\"https://erc.europa.eu/apply-grant/synergy-grant\">ERC SyG webpage</a></li>\r\n</ul>", "image_description": "", "creation_date": "2025-03-26T17:32:18", "last_modification_date": "2025-11-17T14:28:11", "link_label": "", "link_url": "", "canceled": "False", "cancel_reason": "", "place_and_room": "", "url_place_and_room": "", "url_online_room": "", "spoken_languages": [], "speaker": "", "organizer": "", "contact": "[email protected]", "is_internal": "False", "theme": "", "vulgarization": { "id": 1, "fr_label": "Tout public", "en_label": "General public" }, "registration": { "id": 3, "fr_label": "Entrée libre", "en_label": "Free" }, "keywords": "", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/116139/", "category": { "id": 16, "code": "PROP", "fr_label": "Appel à proposition", "en_label": "Call for proposal", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/140/?format=api" ] } ] }
