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{ "count": 238, "next": "https://memento.epfl.ch/api/v1/events/?format=api&limit=10&offset=90&ordering=-event__spoken_languages", "previous": "https://memento.epfl.ch/api/v1/events/?format=api&limit=10&offset=70&ordering=-event__spoken_languages", "results": [ { "id": 70954, "title": "SpectroDynamics 2026: Connecting Computational Spectroscopic Methods Across the Electromagnetic Spectrum", "slug": "spectrodynamics-2026-connecting-computational-sp-2", "event_url": "https://memento.epfl.ch/event/spectrodynamics-2026-connecting-computational-sp-2", "visual_url": "https://memento.epfl.ch/image/32342/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/32342/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/32342/max-size.jpg", "lang": "en", "start_date": "2026-09-07", "end_date": "2026-09-11", "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/spectrodynamics-2026-connecting-computational-spectroscopic-methods-across-the-electromagnetic-spectrum-1489\">https://www.cecam.org/workshop-details/spectrodynamics-2026-connecting-computational-spectroscopic-methods-across-the-electromagnetic-spectrum-1489</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\nLight provides one of the most detailed windows into molecules and matter. Modern light sources allow the probing of equilibrium and non-equilibrium phenomena with Å‐level spatial resolution and femto‐ to attosecond temporal precision. Advances in ultrafast laser technology, together with the rise of X-ray free‐electron lasers and next-generation synchrotron sources, have repeatedly pushed the boundaries of spectroscopic methods from low‐frequency collective modes in biomolecules to electronic and core‐level dynamics. An extensive toolbox of linear and multidimensional spectroscopic techniques now spans the entire electromagnetic spectrum. Terahertz (THz) pulses can coherently drive intermolecular and lattice vibrations in solids and soft matter [1], Mid‐IR and Raman methods map vibrational energy (re)distribution in liquids and vibrational signatures of individual modes in complex molecules [2]. Visible spectroscopy tracks ultrafast charge dynamics in chromophores [3] and photochemical molecular pathways [4], while X-ray sources from free-electron lasers and high-harmonic generation setups enabled time-resolved X-ray diffraction of gas‐phase [5] and condensed systems [6].<br>\r\nDespite sharing common scientific goals, the respective communities have traditionally operated in relative disconnection from each other, relying on different approximations, targeting different observables, and employing distinct numerical implementations. This disconnection manifests, among other symptoms, in the fact that schools, conferences, and workshops are often dedicated to a specific frequency window (e.g. IR spectroscopy) or to simulation methods targeting a class of specific processes (e.g. vibrational dynamics). Opportunities for dialogue and the building of a shared language are lacking. In fact, while preparing this proposal, it became evident that even foundational terms like ab initio or quantum dynamics carry different meanings across communities.<br>\r\nTo address this fragmentation, the proposed CECAM school brings together researchers from diverse backgrounds to foster mutual understanding and build lasting conceptual bridges. Over five days, participants will engage with both the theoretical foundations and practical implementations of spectroscopies across different communities. We will highlight the fact that despite their apparent differences, all spectroscopic methods can be traced back to a common starting point: a light–matter Hamiltonian that includes the quantum description of electronic, nuclear, and photonic degrees of freedom. From this unified framework, we will explore how different approximations—introduced at various stages—lead to the distinct theoretical approaches adopted in each field.<br>\r\nThe first part of the school will focus on approaches that solve the exact quantum molecular dynamics in reduced dimensionality. Within this framework, molecules are treated fully quantum-mechanically, while light is treated classically as an external perturbation within the dipole approximation. From the matter perspective, this means that the full electron + nuclear wavefunction is accessible, offering a great level of detail and information, and the accurate treatment of non-Born-Oppenheimer dynamics. From the light perspective, this means that spectroscopic signals are conveniently calculated via the response function approach (RFA) [7], which is however only valid in the weak field limit. Recently, the RFA has been used to design and simulate several spectroscopic signals of femtosecond molecular photochemistry using novel X-ray pulse sources [8], including stimulated X-ray Raman [9], transient X-ray absorption and transmission [10], and many others [11].<br>\r\nIn the second part, we will shift the focus to longer time scales with more degrees of freedom and study larger molecules in explicit environments (solvent, substrate, etc). In these cases, it is common practice to apply the Born-Oppenheimer approximation and take the classical limit for the nuclei, while keeping the electrons quantum, leading to (finite temperature) molecular dynamics (MD) approaches. To make these simulations computationally tractable, while retaining an explicit description of the electrons, electron–electron interactions are typically simplified using ground-state density functional theory (DFT). This approach, commonly referred to as ab initio molecular dynamics (AIMD), enables the simulation of vibrational spectroscopies such as infrared (IR) and Raman [12,13], as well as surface-specific techniques like sum-frequency generation (SFG) [14,15]. To access larger system sizes and longer simulation timescales, forces can be derived from classical interatomic potentials, facilitating the convergence of multidimensional spectroscopic observables such as THz-Raman spectra [16]. Alternatively, forces can be learned directly from first-principles data using machine-learning (ML) models, enabling ML-driven molecular dynamics and spectroscopy [17-21]. Through path integral techniques, the quantum nature of the nuclei can be recovered, which is particularly important for systems containing light atoms, such as hydrogen [22-24].<br>\r\nThe third part of the school will explore what happens when the primary interest shifts from vibrational to electronic dynamics. In this context, the electron dynamics at the DFT level can be incorporated by considering its time-dependent version (TDDFT), where the exchange-correlation functionals are usually adiabatic. With this method, UV-visible absorption [25], circular dichroism [26], inelastic X-ray scattering, and electron energy loss [27], and other spectroscopies can be computed. Finally, there are situations in which strong light-matter coupling demands an explicit treatment of the photons [28]. These can be reintroduced either by dressing the Kohn-Sham Hamiltonian with electron-photon exchange-correlation potentials (known as quantum-electrodynamics DFT, or QEDFT) [29] or by a semiclassical treatment of the photons solving Maxwell’s equations (the Maxwell-TDDFT method)[30]. These methods enable the calculation of spectra in cavities or arbitrary electromagnetic environments [31], and can account for polaritonic phenomena, radiative lifetimes, superradiance, and many more.<br>\r\nThis school brings together leading experts from exact quantum dynamics, ab initio MD, ML‐enabled simulations, and Maxwell–TDDFT to forge a common language and cross‐fertilize ideas. Lectures will cover both the fundamental principles and the latest advances in each area, highlighting current applications and open challenges. Complementing the lectures, hands-on tutorials will reinforce foundational concepts and provide important hands-on experience on several popular computational approaches (see hands-on section below).<br>\r\nBy spanning the electromagnetic spectrum and the hierarchy of theoretical methods, this school will equip PhD students and postdocs with a unified, multi‐scale, and inter-community perspective on quantum dynamics and spectroscopy. Participants will leave with both a solid grounding in foundational techniques and direct experience of the latest computational frontiers, ready to tackle open challenges in molecular and materials science.<br>\r\n<br>\r\n<strong>References</strong><br>\r\n<br>\r\n<a href=\"https://doi.org/10.1063/1.4901216\" target=\"_blank\">[1] P. Hamm, The Journal of Chemical Physics, <strong>141</strong>, (2014)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jctc.3c00967\" target=\"_blank\">[2] M. Svendsen, K. Thygesen, A. Rubio, J. Flick, J. Chem. Theory Comput., <strong>20</strong>, 926-936 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1103/physrevb.111.085114\" target=\"_blank\">[3] F. Bonafé, E. Albar, S. Ohlmann, V. Kosheleva, C. Bustamante, F. Troisi, A. Rubio, H. Appel, Phys. Rev. B, <strong>111</strong>, 085114 (2025)</a><br>\r\n<a href=\"https://doi.org/10.1103/physreva.90.012508\" target=\"_blank\">[4] M. Ruggenthaler, J. Flick, C. Pellegrini, H. Appel, I. Tokatly, A. Rubio, Phys. Rev. A, <strong>90</strong>, 012508 (2014)</a><br>\r\n<a href=\"https://doi.org/10.1021/acsphotonics.9b00768\" target=\"_blank\">[5] J. Flick, D. Welakuh, M. Ruggenthaler, H. Appel, A. Rubio, ACS Photonics, <strong>6</strong>, 2757-2778 (2019)</a><br>\r\n<a href=\"https://doi.org/10.1063/1.3503594\" target=\"_blank\">[6] A. Sakko, A. Rubio, M. Hakala, K. Hämäläinen, The Journal of Chemical Physics, <strong>133</strong>, (2010)</a><br>\r\n<a href=\"https://doi.org/10.1039/b903200b\" target=\"_blank\">[7] D. Varsano, L. Espinosa-Leal, X. Andrade, M. Marques, R. di Felice, A. Rubio, Phys. Chem. Chem. Phys., <strong>11</strong>, 4481 (2009)</a><br>\r\n<a href=\"https://doi.org/10.1103/physrevb.54.4484\" target=\"_blank\">[8] K. Yabana, G. Bertsch, Phys. Rev. B, <strong>54</strong>, 4484-4487 (1996)</a><br>\r\n<a href=\"https://doi.org/10.1039/c9fd00056a\" target=\"_blank\">[9] Y. Litman, J. Behler, M. Rossi, Faraday Discuss., <strong>221</strong>, 526-546 (2020)</a><br>\r\n<a href=\"https://doi.org/10.1146/annurev-physchem-090722-124705\" target=\"_blank\">[10] S. Althorpe, Annual Review of Physical Chemistry, <strong>75</strong>, 397-420 (2024)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.chemrev.5b00674\" target=\"_blank\">[11] M. Ceriotti, W. Fang, P. Kusalik, R. McKenzie, A. Michaelides, M. Morales, T. Markland, Chem. Rev., <strong>116</strong>, 7529-7550 (2016)</a><br>\r\n<a href=\"https://doi.org/10.1039/c7sc02267k\" target=\"_blank\">[12] M. Gastegger, J. Behler, P. Marquetand, Chem. Sci., <strong>8</strong>, 6924-6935 (2017)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jpca.1c10417\" target=\"_blank\">[13] R. Han, R. Ketkaew, S. Luber, J. Phys. Chem. A, <strong>126</strong>, 801-812 (2022)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jpclett.3c00398\" target=\"_blank\">[14] K. Inoue, Y. Litman, D. Wilkins, Y. Nagata, M. Okuno, J. Phys. Chem. Lett., <strong>14</strong>, 3063-3068 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jpclett.8b00133\" target=\"_blank\">[15] T. Morawietz, O. Marsalek, S. Pattenaude, L. Streacker, D. Ben-Amotz, T. Markland, J. Phys. Chem. Lett., <strong>9</strong>, 851-857 (2018)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jpclett.3c01989\" target=\"_blank\">[16] Y. Litman, J. Lan, Y. Nagata, D. Wilkins, J. Phys. Chem. Lett., <strong>14</strong>, 8175-8182 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1364/aop.8.000401\" target=\"_blank\">[17] D. Nicoletti, A. Cavalleri, Adv. Opt. Photon., <strong>8</strong>, 401 (2016)</a><br>\r\n<a href=\"https://doi.org/10.1063/1.4931106\" target=\"_blank\">[18] T. Ohto, K. Usui, T. Hasegawa, M. Bonn, Y. Nagata, The Journal of Chemical Physics, <strong>143</strong>, (2015)</a><br>\r\n<a href=\"https://doi.org/10.1021/jz301858g\" target=\"_blank\">[19] M. Sulpizi, M. Salanne, M. Sprik, M. Gaigeot, J. Phys. Chem. Lett., <strong>4</strong>, 83-87 (2012)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jpclett.7b00391\" target=\"_blank\">[20] O. Marsalek, T. Markland, J. Phys. Chem. Lett., <strong>8</strong>, 1545-1551 (2017)</a><br>\r\n<a href=\"https://doi.org/10.1021/ct2000952\" target=\"_blank\">[21] C. Zhang, D. Donadio, F. Gygi, G. Galli, J. Chem. Theory Comput., <strong>7</strong>, 1443-1449 (2011)</a><br>\r\n<a href=\"https://doi.org/10.1146/annurev-physchem-062322-051532\" target=\"_blank\">[22] D. Keefer, S. Cavaletto, J. Rouxel, M. Garavelli, H. Yong, S. Mukamel, Annu. Rev. Phys. Chem., <strong>74</strong>, 73-97 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.jctc.3c00062\" target=\"_blank\">[23] S. Cavaletto, Y. Nam, J. Rouxel, D. Keefer, H. Yong, S. Mukamel, J. Chem. Theory Comput., <strong>19</strong>, 2327-2339 (2023)</a><br>\r\n<a href=\"https://doi.org/10.1073/pnas.2015988117\" target=\"_blank\">[24] D. Keefer, T. Schnappinger, R. de Vivie-Riedle, S. Mukamel, Proc. Natl. Acad. Sci. U.S.A., <strong>117</strong>, 24069-24075 (2020)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.chemrev.7b00081\" target=\"_blank\">[25] M. Kowalewski, B. Fingerhut, K. Dorfman, K. Bennett, S. Mukamel, Chem. Rev., <strong>117</strong>, 12165-12226 (2017)</a><br>\r\n[26] Shaul Mukamel, Principles of nonlinear optical spectroscopy, Oxford University Press, New York 1995<br>\r\n<a href=\"https://doi.org/10.1038/s41586-020-2417-3\" target=\"_blank\">[27] J. Kim, S. Nozawa, H. Kim, E. Choi, T. Sato, T. Kim, K. Kim, H. Ki, J. Kim, M. Choi, Y. Lee, J. Heo, K. Oang, K. Ichiyanagi, R. Fukaya, J. Lee, J. Park, I. Eom, S. Chun, S. Kim, M. Kim, T. Katayama, T. Togashi, S. Owada, M. Yabashi, S. Lee, S. Lee, C. Ahn, D. Ahn, J. Moon, S. Choi, J. Kim, T. Joo, J. Kim, S. Adachi, H. Ihee, Nature, <strong>582</strong>, 520-524 (2020)</a><br>\r\n<a href=\"https://doi.org/10.1103/physrevlett.114.255501\" target=\"_blank\">[28] M. Minitti, J. Budarz, A. Kirrander, J. Robinson, D. Ratner, T. Lane, D. Zhu, J. Glownia, M. Kozina, H. Lemke, M. Sikorski, Y. Feng, S. Nelson, K. Saita, B. Stankus, T. Northey, J. Hastings, P. Weber, Phys. Rev. Lett., <strong>114</strong>, 255501 (2015)</a><br>\r\n<a href=\"https://doi.org/10.1038/nature09346\" target=\"_blank\">[29] D. Polli, P. Altoè, O. Weingart, K. Spillane, C. Manzoni, D. Brida, G. Tomasello, G. Orlandi, P. Kukura, R. Mathies, M. Garavelli, G. Cerullo, Nature, <strong>467</strong>, 440-443 (2010)</a><br>\r\n<a href=\"https://doi.org/10.1039/d2fd00014h\" target=\"_blank\">[30] D. Brey, R. Binder, R. Martinazzo, I. Burghardt, Faraday Discuss., <strong>237</strong>, 148-167 (2022)</a><br>\r\n<a href=\"https://doi.org/10.1021/acs.chemrev.9b00813\" target=\"_blank\">[31] C. Baiz, B. Błasiak, J. Bredenbeck, M. Cho, J. Choi, S. Corcelli, A. Dijkstra, C. Feng, S. Garrett-Roe, N. Ge, M. Hanson-Heine, J. Hirst, T. Jansen, K. Kwac, K. Kubarych, C. Londergan, H. Maekawa, M. Reppert, S. Saito, S. Roy, J. Skinner, G. Stock, J. Straub, M. Thielges, K. Tominaga, A. Tokmakoff, H. Torii, L. Wang, L. Webb, M. Zanni, Chem. Rev., <strong>120</strong>, 7152-7218 (2020)</a></p>", "image_description": "", "creation_date": "2026-01-26T15:20:44", "last_modification_date": "2026-01-26T16:44:05", "link_label": "SpectroDynamics 2026: Connecting Computational Spectroscopic Methods Across the Electromagnetic Spec", "link_url": "https://www.cecam.org/workshop-details/spectrodynamics-2026-connecting-computational-spectroscopic-methods-across-the-electromagnetic-spectrum-1489", "canceled": "False", "cancel_reason": "", "place_and_room": "BCH 2103", "url_place_and_room": "https://plan.epfl.ch/?room==BCH%202103", "url_online_room": "", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "", "organizer": "<strong>Franco Bonafé</strong>, Max Planck Institute for the Structure and Dynamics of Matter ; <strong>Daniel Keefer,</strong> Max Planck Institute for Polymer Research ; <strong>Yair Litman</strong>, Max Planck Institute for Polymer Research", "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/119447/", "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": 70955, "title": "Bridging Biomolecular Simulations and Experiments Across Time and Length Scales: from Single Molecules to Entire Organelles", "slug": "bridging-biomolecular-simulations-and-experiments", "event_url": "https://memento.epfl.ch/event/bridging-biomolecular-simulations-and-experiments", "visual_url": "https://memento.epfl.ch/image/32343/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/32343/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/32343/max-size.jpg", "lang": "en", "start_date": "2026-09-14", "end_date": "2026-09-17", "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/bridging-biomolecular-simulations-and-experiments-across-time-and-length-scales-from-single-molecules-to-entire-organelles-1493\">https://www.cecam.org/workshop-details/bridging-biomolecular-simulations-and-experiments-across-time-and-length-scales-from-single-molecules-to-entire-organelles-1493</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\nMolecular simulations are firmly established as a central tool in the life sciences over the last few decades. This is evident from the now-standard use of molecular dynamics simulations by molecular biologists and biophysicists, and the remarkable success of AlphaFold, which has convinced even the most skeptical of the critical role of these methods in contemporary biological research.<br>\r\nHowever, new challenges are emerging. It is increasingly apparent that to understand biomolecular function, we must move beyond studying isolated molecules. The focus is now shifting towards examining large, dynamic complexes of biomolecules within their complex native environments, complete with post-translational modifications. Embracing this complexity is crucial for understanding how biological functions and cellular structures emerge and adapt.<br>\r\nThis workshop will address existing and emerging frontiers, discussing both current challenges and the future of molecular simulations needed to meet them. It will gather simulation experts that have been actively developing methods that can increase simulation accuracy and extend their applicability range across multiple scales, as well as experimentalists performing advanced studies that can address outstanding challenges occurring at computationally accessible time and length scales. A main aim will be to discuss how to improve the accuracy of simulations, integrate simulations and cutting-edge experiments, and how to best take advantage of innovative enhanced sampling and machine learning-based approaches.<br>\r\nThe workshop will seize the opportunity to celebrate the outstanding scientific achievements of Gerhard Hummer, a prominent leader in the field, on his sixty’s birthday. Many of the participants that have already expressed their intention to attend and support the workshop or past or current theoretical and experimental scientist that have been either collaborators and co-authors, mentored by, or inspired by Gerhard’s ideas and expertise.</p>", "image_description": "", "creation_date": "2026-01-26T15:39:35", "last_modification_date": "2026-01-26T16:44:37", "link_label": "Bridging Biomolecular Simulations and Experiments Across Time and Length Scales: from Single Molecul", "link_url": "https://www.cecam.org/workshop-details/bridging-biomolecular-simulations-and-experiments-across-time-and-length-scales-from-single-molecules-to-entire-organelles-1493", "canceled": "False", "cancel_reason": "", "place_and_room": "BCH 2103", "url_place_and_room": "https://plan.epfl.ch/?room==BCH%202103", "url_online_room": "", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "", "organizer": "<strong>Nicolae-Viorel Buchete</strong>, University College Dublin ; <strong>Pilar Cossio</strong>, Flatiron Institute ; <strong>Roberto Covino</strong>, Goethe University Frankfurt -- Frankfurt Institute for Advanced Studies ; <strong>Ville Kaila</strong>, Stockholm University ; <strong>Edina Rosta</strong>, University College London", "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/119449/", "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" ] }, { "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": 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": 70974, "title": "Brown Bag Seminar in Finance", "slug": "brown-bag-seminar-in-finance-13", "event_url": "https://memento.epfl.ch/event/brown-bag-seminar-in-finance-13", "visual_url": "https://memento.epfl.ch/image/32361/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/32361/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/32361/max-size.jpg", "lang": "en", "start_date": "2026-06-16", "end_date": "2026-06-16", "start_time": "12:15:00", "end_time": "13:15:00", "description": "", "image_description": "", "creation_date": "2026-01-27T10:56:12", "last_modification_date": "2026-01-27T10:56:12", "link_label": "", "link_url": "", "canceled": "False", "cancel_reason": "", "place_and_room": "UNIL, Extranef, room 126", "url_place_and_room": "", "url_online_room": "", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "<a href=\"https://profiles.imperial.ac.uk/yang.liu19\">Mingyang Liu - PhD student, Imperial College London</a>", "organizer": "", "contact": "[email protected]\r\n\r\n ", "is_internal": "False", "theme": "", "vulgarization": { "id": 2, "fr_label": "Public averti", "en_label": "Informed public" }, "registration": { "id": 2, "fr_label": "Sur invitation", "en_label": "Invitation required" }, "keywords": "", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/119483/", "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/3/?format=api", "https://memento.epfl.ch/api/v1/mementos/116/?format=api", "https://memento.epfl.ch/api/v1/mementos/39/?format=api", "https://memento.epfl.ch/api/v1/mementos/105/?format=api" ] }, { "id": 70990, "title": "\"Mapping the Human Body One Cell at a Time.\"", "slug": "mapping-the-human-body-one-cell-at-a-time", "event_url": "https://memento.epfl.ch/event/mapping-the-human-body-one-cell-at-a-time", "visual_url": "https://memento.epfl.ch/image/32376/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/32376/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/32376/max-size.jpg", "lang": "en", "start_date": "2026-04-30", "end_date": "2026-04-30", "start_time": "12:15:00", "end_time": "13:15:00", "description": "<strong>A Lola and John Grace Distinguished Lecture in Cancer Research</strong>\r\n<div class=\"elementor-element elementor-element-98cefd8 elementor-widget elementor-widget-heading\">\r\n<div class=\"elementor-widget-container\"><br>\r\nSarah Teichmann completed her PhD at the MRC Laboratory of Molecular Biology in Cambridge, UK, and was a Beit Memorial Fellow at University College London. She established her research group at the MRC Laboratory of Molecular Biology in 2001, where her main discoveries included the finding that protein assembly pathways are stereotypical and conserved. In 2013, she transitioned to the Wellcome Genome Campus, where she became the first and, to date, the only faculty member appointed across both the EMBL-European Bioinformatics Institute and the Wellcome Sanger Institute. In 2016, she was appointed as the Head of the Cellular Genetics programme at the Wellcome Sanger Institute and co-founded the Human Cell Atlas initiative. From April 2024, she was appointed chair in Stem Cell Medicine at the University of Cambridge, within the Department of Medicine and the Cambridge Stem Cell Institute. Additionally, Sarah dedicates part of her time to GlaxoSmithKline and to EnsoCell Therapeutics, the startup company she co-founded. The Teichmann lab focuses on developing and applying cell atlas technologies to understand human tissue architecture, particularly examining how cellular diversity is generated in the immune system and during development.</div>\r\n</div>\r\n\r\n<div class=\"elementor-element elementor-element-e552a16 elementor-widget elementor-widget-text-editor\">\r\n<div class=\"elementor-widget-container\"> </div>\r\n</div>", "image_description": "", "creation_date": "2026-01-28T14:35:28", "last_modification_date": "2026-02-13T13:56:17", "link_label": "", "link_url": "", "canceled": "False", "cancel_reason": "", "place_and_room": "SV 1717", "url_place_and_room": "https://plan.epfl.ch/?room==SV%201717", "url_online_room": "https://epfl.zoom.us/j/97039045251?pwd=WDFjUGV3Y1FxeG9rTUIrOGpiUXhLQT09", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "<strong>Sarah Teichmann FMedSci FRS</strong> (Group Leader), Cambridge Stem Cell Institute & Department of Medicine, Jeffrey Cheah Biomedical Centre, University of Cambridge", "organizer": "Prof. Charlotte Bunne", "contact": "Lisa Smith, ISREC Administrative Assistant", "is_internal": "True", "theme": "", "vulgarization": { "id": 2, "fr_label": "Public averti", "en_label": "Informed public" }, "registration": { "id": 3, "fr_label": "Entrée libre", "en_label": "Free" }, "keywords": "Grace Lecture, cancer", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/119505/", "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/26/?format=api", "https://memento.epfl.ch/api/v1/mementos/9/?format=api", "https://memento.epfl.ch/api/v1/mementos/6/?format=api" ] }, { "id": 70999, "title": "Administrative Management of European Project - ERC and MSCA Projects", "slug": "administrative-management-of-european-project-er-2", "event_url": "https://memento.epfl.ch/event/administrative-management-of-european-project-er-2", "visual_url": "https://memento.epfl.ch/image/32387/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/32387/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/32387/max-size.jpg", "lang": "en", "start_date": "2026-06-11", "end_date": "2026-06-11", "start_time": "09:30:00", "end_time": "12:00:00", "description": "<p>European Framework Programs for Research and Innovation.<br>\r\n<br>\r\nIs your laboratory involved in one or several European projects, and is one of your responsibilities to ensure their effective administrative, financial, and human‑resources management? If so, it is important to take the time to become familiar with the structure of these projects and with the specific management rules that apply to them.<br>\r\n<br>\r\nThis training course will guide you through the contractual documents and their relevant content for project management. Administrative, financial, and HR management rules will be presented and discussed using practical case studies.<br>\r\nThe training will also help participants become familiar with the European portal and the SEFRI reporting platform.<br>\r\n<br>\r\nIt is recommended to attend this training as early as possible, ideally at the start of the project.</p>", "image_description": "", "creation_date": "2026-01-30T10:06:37", "last_modification_date": "2026-01-30T10:07:35", "link_label": "Inscription", "link_url": "https://epfl.eu.crossknowledge.com/site/m/public_training/565", "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": "EU-Funding Team of the Research Office", "organizer": "KeepLearning", "contact": "[email protected]", "is_internal": "True", "theme": "", "vulgarization": { "id": 1, "fr_label": "Tout public", "en_label": "General public" }, "registration": { "id": 1, "fr_label": "Sur inscription", "en_label": "Registration required" }, "keywords": "", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/119521/", "category": { "id": 15, "code": "FORM", "fr_label": "Formations internes", "en_label": "Internal trainings", "activated": true }, "academic_calendar_category": null, "domains": [], "mementos": [ "https://memento.epfl.ch/api/v1/mementos/145/?format=api", "https://memento.epfl.ch/api/v1/mementos/431/?format=api", "https://memento.epfl.ch/api/v1/mementos/6/?format=api" ] }, { "id": 71003, "title": "Imaging Lunch: A Practical Introduction to Machine Learning for Vision Applications", "slug": "imaging-lunch-a-practical-introduction-to-machine", "event_url": "https://memento.epfl.ch/event/imaging-lunch-a-practical-introduction-to-machine", "visual_url": "https://memento.epfl.ch/image/32391/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/32391/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/32391/max-size.jpg", "lang": "en", "start_date": "2026-04-29", "end_date": "2026-04-29", "start_time": "11:00:00", "end_time": "13:00:00", "description": "<strong><a href=\"https://docs.google.com/forms/d/e/1FAIpQLSc1NukuuzIzzMnbDZkfudvj1M7wDJY6JeWQKoQrcl1ZIVFcUw/viewform?usp=header\">Registration</a><br>\r\n<br>\r\nAbstract</strong><br>\r\nThis workshop is designed for EPFL researchers interested in building effective, automated computer vision systems for scientific applications. During the workshop, we will review and explain the main steps of a machine learning-based computer vision project, from problem definition to image acquisition, annotation, training, validation, and inference. We will illustrate these steps in a practical way, by building a real computer vision application together until we can run it live on a camera. Along the way, we will discuss important concepts (data drift, overfitting, data augmentation) and observe how they manifest themselves in practice. We will also share tips and tricks to help you tackle your own computer vision challenges.<br>\r\n<br>\r\n<strong>Prerequisites:</strong><br>\r\nBasic familiarity with Python, image analysis, and machine learning concepts is desirable, but not strictly necessary.<br>\r\n<br>\r\n<strong>Level:</strong> <br>\r\nBeginner / Intermediate<br>\r\n ", "image_description": "", "creation_date": "2026-01-30T11:40:06", "last_modification_date": "2026-01-30T11:40:06", "link_label": "Registration", "link_url": "https://docs.google.com/forms/d/e/1FAIpQLSc1NukuuzIzzMnbDZkfudvj1M7wDJY6JeWQKoQrcl1ZIVFcUw/viewform?usp=header", "canceled": "False", "cancel_reason": "", "place_and_room": "CE 1 711.2", "url_place_and_room": "https://plan.epfl.ch/?room==CE%201%20711.2", "url_online_room": "", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "<a href=\"https://people.epfl.ch/mallory.wittwer?lang=en\">Mallory Witwer</a>", "organizer": "<a href=\"https://imaging.epfl.ch/\">Center for Imaging</a>", "contact": "<a href=\"https://people.epfl.ch/cecilia.carron?lang=fr\">Cecilia Carron</a>", "is_internal": "False", "theme": "", "vulgarization": { "id": 1, "fr_label": "Tout public", "en_label": "General public" }, "registration": { "id": 1, "fr_label": "Sur inscription", "en_label": "Registration required" }, "keywords": "", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/119528/", "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/4/?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", "https://memento.epfl.ch/api/v1/mementos/27/?format=api" ] }, { "id": 71009, "title": "BMI Seminar // Sung Han: Revealing the role of neuropeptides in neural circuit function and behavior", "slug": "bmi-seminar-sung-han-revealing-the-role-of-neurope", "event_url": "https://memento.epfl.ch/event/bmi-seminar-sung-han-revealing-the-role-of-neurope", "visual_url": "https://memento.epfl.ch/image/32395/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/32395/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/32395/max-size.jpg", "lang": "en", "start_date": "2026-04-13", "end_date": "2026-04-13", "start_time": "14:00:00", "end_time": "15:00:00", "description": "<p>Neuropeptides play a critical role in modulating neural circuits and influencing behavior, yet their precise mechanisms of action remain largely unexplored. In this talk, I will present our latest findings on the role of neuropeptides in neural circuit function, uncovered through the use of novel genetically encoded sensors and silencers designed specifically for peptidergic transmission. By applying these innovative tools, we have identified key pathways and mechanisms by which neuropeptides regulate neuronal activity and orchestrate complex behavioral responses. This presentation will highlight the biological insights gained from these studies, offering a deeper understanding of how neuropeptide signaling shapes brain function and behavior.<br>\r\n </p>", "image_description": "", "creation_date": "2026-01-30T16:01:35", "last_modification_date": "2026-02-10T16:25:35", "link_label": "Web Page", "link_url": "https://www.salk.edu/scientist/sung-han/", "canceled": "False", "cancel_reason": "", "place_and_room": "SV 1717", "url_place_and_room": "https://plan.epfl.ch/?room==SV%201717", "url_online_room": "https://epfl.zoom.us/j/64813563657", "spoken_languages": [ "https://memento.epfl.ch/api/v1/spoken_languages/2/?format=api" ], "speaker": "Sung Han, Salk Institute for Biological Studies", "organizer": "<strong>BMI LSYM</strong> <strong>Host: Ralf Schneggenburger</strong>", "contact": "[email protected]", "is_internal": "False", "theme": "", "vulgarization": { "id": 2, "fr_label": "Public averti", "en_label": "Informed public" }, "registration": { "id": 3, "fr_label": "Entrée libre", "en_label": "Free" }, "keywords": "", "file": null, "icalendar_url": "https://memento.epfl.ch/event/export/119537/", "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/19/?format=api", "https://memento.epfl.ch/api/v1/mementos/9/?format=api", "https://memento.epfl.ch/api/v1/mementos/6/?format=api" ] }, { "id": 71019, "title": "Summer School in Image Analysis", "slug": "summer-school-in-image-analysis-2", "event_url": "https://memento.epfl.ch/event/summer-school-in-image-analysis-2", "visual_url": "https://memento.epfl.ch/image/32406/200x112.jpg", "visual_large_url": "https://memento.epfl.ch/image/32406/720x405.jpg", "visual_maxsize_url": "https://memento.epfl.ch/image/32406/max-size.jpg", "lang": "en", "start_date": "2026-06-08", "end_date": "2026-06-12", "start_time": null, "end_time": null, "description": "<p>A hands-on introduction to the key concepts in image analysis for your everyday research! <br>\r\n<br>\r\nOpen to PhD students from all doctoral programs at EPFL, Swiss academic institutions and ETH domain.<br>\r\n<br>\r\n<strong>June 8 to 12 2026 </strong><br>\r\n<strong>Palace de Caux, Montreux</strong><br>\r\nPre-summer school Workshop will take place on June 4, 2026 (afternoon)<br>\r\n<br>\r\n<strong><a href=\"https://imaging.epfl.ch/summer-school\">More info</a></strong><br>\r\n<strong><a href=\"https://docs.google.com/forms/d/e/1FAIpQLSdtHQLlAolAnXJHI5BKbgJXUJA5F6seAPbIOT7W1zKvkZ90wQ/viewform?usp=header\">Application</a></strong> Deadline: March 1, 2026<br>\r\n<br>\r\nAre you a PhD student at EPFL, at another swiss academic institution or within the ETH domaine who regularly faces questions regarding the analysis of your images ? Do you want to learn more about practical concepts and tools to help you in this endeavor? Then our summer school in image analysis is for you! Throughout the week, a series of lectures will provide you with the essential concepts in image analysis – from the nature of digital images through the physics of image acquisition to the basics of deep learning, and more. In addition to these lectures, you will learn to use some popular image-analysis software during practical sessions.</p>", "image_description": "", "creation_date": "2026-02-03T09:47:28", "last_modification_date": "2026-02-03T10:01:52", "link_label": "Summer School in Imaging", "link_url": "https://imaging.epfl.ch/summer-school", "canceled": "False", "cancel_reason": "", "place_and_room": "Palace de Caux, Montreux", "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://imaging.epfl.ch/\">Center for Imaging</a>", "contact": "[email protected]", "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/119553/", "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/4/?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", "https://memento.epfl.ch/api/v1/mementos/27/?format=api" ] } ] }
