![\"\"](\"//memento.epfl.ch/public/upload/fckeditorimage/c2/f6/c5e48d79.jpg\")
\r\nJoin us for the third edition of the Lemanic Life Sciences Hackathon!
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\r\nOrganized by EPFL School of Life Sciences, EPFL AI Center and the University of Bern, we aim to bring together clinicians, life scientists, and data scientists to test ideas, drive innovation, and tackle real-world challenges in healthcare and research.
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\r\nExplore the untapped potential of AI in life sciences and clinical research\r\n
\r\nFrom digital puzzles to space simulations, play has become a major arena for creation, innovation, and reflection. Through a curated selection of video games, history books, essays, and academic research, the Library invites you to discover the many dimensions of games and gaming culture. Borrow the documents and keep the experience going at home!
","image_description":"CC-BY-NC-SA EPFL Library","creation_date":"2026-03-18T09:56:25","last_modification_date":"2026-03-18T09:56:55","link_label":"Sélection documentaire en ligne","link_url":"https://slsp-epfl.primo.exlibrisgroup.com/discovery/collectionDiscovery?vid=41SLSP_EPF:prod&collectionId=8196759420005516&lang=fr","canceled":"False","cancel_reason":"","place_and_room":"Espace Découverte","url_place_and_room":"","url_online_room":"","spoken_languages":["https://memento.epfl.ch/api/v1/spoken_languages/1/?format=json","https://memento.epfl.ch/api/v1/spoken_languages/2/?format=json"],"speaker":"","organizer":"EPFL Library","contact":"library@epfl.ch","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":"Jeux, jeux vidéo, théorie des jeux","file":null,"icalendar_url":"https://memento.epfl.ch/event/export/120117/","category":{"id":5,"code":"EXPO","fr_label":"Expositions","en_label":"Exhibitions","activated":true},"academic_calendar_category":null,"domains":[],"mementos":["https://memento.epfl.ch/api/v1/mementos/1/?format=json","https://memento.epfl.ch/api/v1/mementos/3/?format=json","https://memento.epfl.ch/api/v1/mementos/5/?format=json","https://memento.epfl.ch/api/v1/mementos/6/?format=json","https://memento.epfl.ch/api/v1/mementos/8/?format=json","https://memento.epfl.ch/api/v1/mementos/145/?format=json","https://memento.epfl.ch/api/v1/mementos/275/?format=json","https://memento.epfl.ch/api/v1/mementos/22/?format=json","https://memento.epfl.ch/api/v1/mementos/27/?format=json"]},{"id":71389,"title":"Call for projects CROSS 2027","slug":"call-for-projects-cross-2027","event_url":"https://memento.epfl.ch/event/call-for-projects-cross-2027","visual_url":"https://memento.epfl.ch/image/32738/200x112.jpg","visual_large_url":"https://memento.epfl.ch/image/32738/720x405.jpg","visual_maxsize_url":"https://memento.epfl.ch/image/32738/max-size.jpg","lang":"en","start_date":"2026-03-18","end_date":"2026-06-15","start_time":"00:00:00","end_time":"23:59:00","description":"The 2027 edition of the CROSS program calls upon researchers at EPFL and the University of Lausanne to submit proposals for joint projects that bring the natural sciences and engineering together with the social sciences and humanities.
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\r\nThrough this annual call for projects, CROSS provides competitive grants to support new seed research endeavors that have the potential to grow into full–scale interdisciplinary research projects.
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\r\nThe 2024 CROSS call is open to all topics.
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\r\nPROPOSALS:
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\r\nProposals must come from joint UNIL-EPFL teams, which bring together specialists in the human and social sciences on the one hand, with specialists from life sciences, natural sciences or engineering on the other. Up to six projects will be selected, with a maximum of CHF 60,000 awarded per project.\r\n
A reason for the interest in multiferroics is that magnetic and electric orders do not simply exist side by side, but exhibit \"added value\" in the form of magnetoelectric interactions and functionalities between the ordered states. Likewise, in a ferroic material, regions with different orientation of the order parameter, the domains, do not simply exist side by side, but they exhibit new phases and properties in the domain walls. Because of their discontinuous, confined, and topological nature, domain walls exhibit functional states that are not possible in the bulk. Continuing this line of thought, one should expect domain walls in multiferroics to be a particularly rich source of novel phenomena. Here one must distinguish between (i) \"domain walls in multiferroics\", where only the ferroelectric (or magnetic) order is considered so that little is learned about the multiferroic state, and (ii) \"multiferroic domain walls\" where the ferroic phase coexistence of the wall itself is of interest. The latter are rarely studied, and I will discuss some of their intriguing features in my talk.
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\r\nBio: Professor Manfred Fiebig is known for his work in light-matter interaction in systems with strong electronic correlations. (Multi-) ferroics are of particular interest to him. After obtaining his doctoral degree in physics at the University of Dortmund, he worked at the University of Tokyo, the Max Born Institut Berlin, and the University of Bonn before he was appointed as Professor of Multifunctional Ferroic Materials in the Department of Materials at ETH Zurich in 2011. In 2021 he also became a member of the National Research Council of the Swiss National Science Foundation (SNSF), and he was elected as Corresponding Member of the Academy of Sciences and Literature | Mainz. Most recent distinctions include the 2022 APS Frank Isakson Prize for Optical Effects in Solids as well as the of the Stern Gerlach Medal in 2023, the highest distinction in Experimental Physics of the German Physical Society. He is one of the founders of the ETH Spinoff Company “3Wave Instruments”.
In this seminar, I will discuss our efforts to design conformationally constrained helical macrocyclic peptides and outline the principles that enable effective targeting of protein–protein interactions beyond classical stapled peptides. In the second part, I will show how a subtle isosteric backbone modification—thioamidation—can be used to impart oral bioavailability to bioactive macrocyclic peptides. I will further illustrate how conformational restriction enhances membrane permeability and highlight the critical role of metabolic stability in achieving oral bioavailability.
","image_description":"Prof. Jayanta Chatterjee","creation_date":"2026-03-30T19:14:23","last_modification_date":"2026-03-30T19:24:00","link_label":"Publications Prof. Jayanta Chatterjee","link_url":"https://scholar.google.com/citations?user=r0aQPNIAAAAJ&hl=en","canceled":"False","cancel_reason":"","place_and_room":"BCH 3118","url_place_and_room":"https://plan.epfl.ch/?room==BCH%203118","url_online_room":"","spoken_languages":["https://memento.epfl.ch/api/v1/spoken_languages/2/?format=json"],"speaker":"Prof. Jayanta Chatterjee, Indian Institute of Science, Bangalore, India","organizer":"C. Heinis","contact":"C. Heinis","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":"cbseminar","file":null,"icalendar_url":"https://memento.epfl.ch/event/export/120241/","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/9/?format=json","https://memento.epfl.ch/api/v1/mementos/5/?format=json","https://memento.epfl.ch/api/v1/mementos/14/?format=json"]},{"id":70900,"title":"FAIR Data Management of Theoretical Spectroscopy and Green’s Function Methods","slug":"fair-data-management-of-theoretical-spectroscopy-a","event_url":"https://memento.epfl.ch/event/fair-data-management-of-theoretical-spectroscopy-a","visual_url":"https://memento.epfl.ch/image/32289/200x112.jpg","visual_large_url":"https://memento.epfl.ch/image/32289/720x405.jpg","visual_maxsize_url":"https://memento.epfl.ch/image/32289/max-size.jpg","lang":"en","start_date":"2026-04-20","end_date":"2026-04-24","start_time":null,"end_time":null,"description":"You can apply to participate and find all the relevant information (speakers, abstracts, program,...) on the event website: https://www.cecam.org/workshop-details/fair-data-management-of-theoretical-spectroscopy-and-greens-function-methods-1377.
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\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 CECAM Event Manager if you have any question.
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\r\nDescription
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\r\nBig-data-driven methodologies have emerged as a fundamental paradigm of science, but require an enormous amount of resources to achieve their promised impact. The FAIR (Findable, Accessible, Interoperable, and Reusable) data principles [1] ensure that scientific data can be shared and reutilized, providing an efficient route for accumulating data and taking advantage of these powerful techniques. FAIR data management allows essential knowledge to be systematically extracted from data, accelerating discoveries and innovations across various domains [2]. Furthermore, open science is essential for the verifiability and reproducibility of results and has been a topic of major discussion over the last decade. In materials science, data-driven methodologies, coupled with the appropriate FAIR data management practices, are invaluable for the discovery of new materials due to the vast combinatorial space of chemical systems that emerge from the periodic table [3, 4]. Such methodologies have been successfully applied, e.g., to design and predict new materials with desired properties using ab-initio ground state simulations, i.e., data generated from Density Functional Theory (DFT) calculations [5]. However, there remains a critical gap in replicating this success in the context of other simulation frameworks.
\r\nTheoretical spectroscopy and Green's function method simulations [6, 7], including data simulated using the GW approximation, Time-Dependent Density Functional Theory (TDDFT), the Bethe-Salpeter equation (BSE), Dynamical Mean-Field Theory (DMFT), and Korringa-Kohn-Rostoker (KKR), pose especially difficult challenges in the context of FAIR data management. These simulations not only involve extensive computational resources and produce large datasets with associated complex workflows but are also executed using a large variety of public and in-house simulation software. At the same time, these methodologies are essential for understanding excited state properties of complex materials; they are more accurate than DFT calculations and provide better comparisons with experimental results since they incorporate excited states and electronic correlation effects in a more consistent manner [8].
\r\nThere has recently been a number of individual efforts to improve the accessibility of data produced by theoretical spectroscopy and Green’s function methods through the usage of publicly accessible databases. For example, the Computational Materials Repository (CMR) [9] contains several individual databases, amongst which the Computational 2D Materials Database (C2DB) [10] contains GW and BSE data for a specific set of parameters and properties. The MaterialsCloud [11] database has some individual datasets published for these methodologies, however there is not a clear data structure for them. The NIST-JARVIS [12] database has a specific app for BeyondDFT simulations with DMFT data, but only for a specific simulation code. By making datasets findable, these efforts aim to avoid redundant computations and thus build upon existing work more efficiently. While these efforts represent an important step in the right direction, they fall short of fully achieving their goal due to a continued lack of consistency (i.e., interoperability) between individual databases. Moreover, these self-managed databases typically lack the ability to store the complete provenance of the simulated workflow, which is essential to ensure reproducibility.
\r\nRecently, FAIRmat [13], a consortium of the German research data infrastructure (NFDI) association, was formed to construct a scalable data infrastructure for Materials Science that can be easily customized for individual communities. This infrastructure consists of a primary software and repository called NOMAD [14]—a free web-service that enables the organization, analysis, sharing, and publishing of materials science data. One of the tasks within FAIRmat’s scope is to build support for theoretical spectroscopy and Green’s function simulations within NOMAD. Support for several of these methodologies have now been successfully built, and there already exists over 10 000 entries in the NOMAD repository containing GW [15], BSE [16], and DMFT [17] data, along with the full provenance of the corresponding complex workflows. The next step to developing a FAIR data infrastructure for these methods is to tackle the interoperability problem.
\r\nInteroperability within this domain is extremely challenging due to the heterogeneous character of theoretical spectroscopy and Green’s function simulations. Consequently, the adoption of common structures (e.g., describing the Green’s function, the self-energy, or the dielectric function) is the key for improving interoperability. Thus, various members of the community, including method developers, materials and data scientists, and data management experts, must come together to reach a consensus on specific common data structures.
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\r\nReferences
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\r\n[1] Computational Materials Repository (CMR) website
\r\n[2] S. Di Cataldo, P. Worm, J. Tomczak, L. Si, K. Held, Nat. Commun., 15, 3952 (2024)
\r\n[3] F. Meng, B. Maurer, F. Peschel, S. Selcuk, M. Hybertsen, X. Qu, C. Vorwerk, C. Draxl, J. Vinson, D. Lu, Phys. Rev. Materials, 8, 013801 (2024)
\r\n[4] M. van Setten, F. Caruso, S. Sharifzadeh, X. Ren, M. Scheffler, F. Liu, J. Lischner, L. Lin, J. Deslippe, S. Louie, C. Yang, F. Weigend, J. Neaton, F. Evers, P. Rinke, J. Chem. Theory Comput., 11, 5665-5687 (2015)
\r\n[5] M. Scheidgen, L. Himanen, A. Ladines, D. Sikter, M. Nakhaee, Á. Fekete, T. Chang, A. Golparvar, J. Márquez, S. Brockhauser, S. Brückner, L. Ghiringhelli, F. Dietrich, D. Lehmberg, T. Denell, A. Albino, H. Näsström, S. Shabih, F. Dobener, M. Kühbach, R. Mozumder, J. Rudzinski, N. Daelman, J. Pizarro, M. Kuban, C. Salazar, P. Ondračka, H. Bungartz, C. Draxl, JOSS., 8, 5388 (2023)
\r\n[6] FAIRmat website
\r\n[7] K. Choudhary, K. Garrity, A. Reid, B. DeCost, A. Biacchi, A. Hight Walker, Z. Trautt, J. Hattrick-Simpers, A. Kusne, A. Centrone, A. Davydov, J. Jiang, R. Pachter, G. Cheon, E. Reed, A. Agrawal, X. Qian, V. Sharma, H. Zhuang, S. Kalinin, B. Sumpter, G. Pilania, P. Acar, S. Mandal, K. Haule, D. Vanderbilt, K. Rabe, F. Tavazza, npj. Comput. Mater., 6, 173 (2020)
\r\n[8] L. Talirz, S. Kumbhar, E. Passaro, A. Yakutovich, V. Granata, F. Gargiulo, M. Borelli, M. Uhrin, S. Huber, S. Zoupanos, C. Adorf, C. Andersen, O. Schütt, C. Pignedoli, D. Passerone, J. VandeVondele, T. Schulthess, B. Smit, G. Pizzi, N. Marzari, Sci. Data., 7, 299 (2020)
\r\n[9] S. Haastrup, M. Strange, M. Pandey, T. Deilmann, P. Schmidt, N. Hinsche, M. Gjerding, D. Torelli, P. Larsen, A. Riis-Jensen, J. Gath, K. Jacobsen, J. Jørgen Mortensen, T. Olsen, K. Thygesen, 2D Mater., 5, 042002 (2018)
\r\n[10] M. Wilkinson, M. Dumontier, I. Aalbersberg, G. Appleton, M. Axton, A. Baak, N. Blomberg, J. Boiten, L. da Silva Santos, P. Bourne, J. Bouwman, A. Brookes, T. Clark, M. Crosas, I. Dillo, O. Dumon, S. Edmunds, C. Evelo, R. Finkers, A. Gonzalez-Beltran, A. Gray, P. Groth, C. Goble, J. Grethe, J. Heringa, P. ’t Hoen, R. Hooft, T. Kuhn, R. Kok, J. Kok, S. Lusher, M. Martone, A. Mons, A. Packer, B. Persson, P. Rocca-Serra, M. Roos, R. van Schaik, S. Sansone, E. Schultes, T. Sengstag, T. Slater, G. Strawn, M. Swertz, M. Thompson, J. van der Lei, E. van Mulligen, J. Velterop, A. Waagmeester, P. Wittenburg, K. Wolstencroft, J. Zhao, B. Mons, Sci. Data., 3, 160018 (2016)
\r\n[11] L. Reining et al., Comptes Rendus Physique 10, 6 (2009)
\r\n[12] V. Blum, R. Asahi, J. Autschbach, C. Bannwarth, G. Bihlmayer, S. Blügel, L. Burns, T. Crawford, W. Dawson, W. de Jong, C. Draxl, C. Filippi, L. Genovese, P. Giannozzi, N. Govind, S. Hammes-Schiffer, J. Hammond, B. Hourahine, A. Jain, Y. Kanai, P. Kent, A. Larsen, S. Lehtola, X. Li, R. Lindh, S. Maeda, N. Makri, J. Moussa, T. Nakajima, J. Nash, M. Oliveira, P. Patel, G. Pizzi, G. Pourtois, B. Pritchard, E. Rabani, M. Reiher, L. Reining, X. Ren, M. Rossi, H. Schlegel, N. Seriani, L. Slipchenko, A. Thom, E. Valeev, B. Van Troeye, L. Visscher, V. Vlcek, H. Werner, D. Williams-Young, T. Windus, Electron. Struct., (2024)
\r\n[13] L. Ghiringhelli, C. Baldauf, T. Bereau, S. Brockhauser, C. Carbogno, J. Chamanara, S. Cozzini, S. Curtarolo, C. Draxl, S. Dwaraknath, Á. Fekete, J. Kermode, C. Koch, M. Kühbach, A. Ladines, P. Lambrix, M. Himmer, S. Levchenko, M. Oliveira, A. Michalchuk, R. Miller, B. Onat, P. Pavone, G. Pizzi, B. Regler, G. Rignanese, J. Schaarschmidt, M. Scheidgen, A. Schneidewind, T. Sheveleva, C. Su, D. Usvyat, O. Valsson, C. Wöll, M. Scheffler, Sci. Data., 10, 626 (2023)
\r\n[14] J. Schmidt, M. Marques, S. Botti, M. Marques, npj. Comput. Mater., 5, 83 (2019)
\r\n[15] L. Himanen, A. Geurts, A. Foster, P. Rinke, Advanced Science, 6, (2019)
\r\n[16] M. Scheffler, M. Aeschlimann, M. Albrecht, T. Bereau, H. Bungartz, C. Felser, M. Greiner, A. Groß, C. Koch, K. Kremer, W. Nagel, M. Scheidgen, C. Wöll, C. Draxl, Nature, 604, 635-642 (2022)
\r\n[17] C. Draxl, M. Scheffler, MRS Bull., 43, 676-682 (2018)
Hosted by Frédéric Grouiller, CIBM MRI HUG-UNIGE Section head, we are pleased to invite you to attend the CIBM 7T MRI Seminar on April 21st at 10:00 CEST by Caroline Le Ster from the CEA Neurospin, Paris who will be sharing on “Leveraging the potential of UHF scanners for fMRI studies”.
\r\nAbstract
\r\nThere is a growing availability of 7T scanners, with approximately 100 systems currently installed worldwide. These ultra-high-filed (UHF) scanners are particularly relevant for neuroimaging, where anatomical and functional images can be acquired with higher spatial and temporal resolution than on conventional scanners. However, UHF scanners remain difficult to operate, and understanding their specific limitations is essential. These systems indeed face several challenges arising from MR physics and biological effects that must be addressed within engineering constraints. Leverage the potential of UHF scanners, for instance through field monitoring, is therefore important to make the most of these scanners and benefit from the intrinsic SNR gain.
\r\nfMRI particularly benefits from the increase in magnetic field strength, enabling studies to be performed at higher resolution than at lower fields. In order to maintain reasonable acquisition times despite larger imaging matrices, several acceleration strategies have been developed, e.g. multi-slice EPI (SMS-EPI), three-dimensional EPI (3D-EPI) and non-Cartesian sampling schemes. In addition, functional contrasts also benefit from the field increase, including improved spatial localization of the BOLD contrast and the possibility to exploit VASO contrast.
Thesis Director: Prof. T. Mountford,
\r\nMathematics doctoral program
\r\nThesis Nr. 11211
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\r\nTo take part in the public defense, please contact directly the speaker
The EPFL AI Center is delighted to invite you to join the exchange session about the Research Computing Platform (RCP).
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\r\nAre you building, training ML models? Are you currently facing challenges regarding IT infrastructure, and looking for reliable, collaborative, high-capacity, and affordable storage solutions to manage your research data? Are you seeking information about the computing costs?
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\r\nThe Research Computing Platform (RCP) offers campus-wide IT infrastructure geared for the research community. The offering includes a GPU infrastructure (> 400) aiming at making AI compute as accessible as possible throughout the campus.
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\r\nThis event will provide insights into the various services RCP offers to the EPFL research community.
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\r\nEvent Details:\r\n