QLS

Europe/Rome 2022-10-31 07:00:00 2022-11-08 21:00:00 ICTP-KIAS School on Statistical Physics for Life Sciences | (smr 3746) Life can be thought of as a type of stochastic information processing realized out of thermodynamic equilibrium. Living systems indeed consume energy to sustain order and information flow in fluctuating environments. Recent advances in non-equilibrium statistical physics and information theory offer a new framework to unravel the underlying principles of the dynamical processes in living matter. As an example of the developing interface between biology, information theory and statistical physics, a recently discovered new principle, the thermodynamic uncertainty relation, quantifies the energy-precision trade-off of biological processes and its physical bounds. Another important example of the richness of this interface is offered by machine learning, which couples ideas from neuroscience, computer science and statistical physics. The new language developed in modern statistical mechanics is then expected to play a key role in the understanding of how order, and eventually life, emerges from disorder. It has been widely demonstrated that statistical mechanics is an essential tool for the development of the above subjects, and great interest in these subjects is currently shared by statistical physics and biophysics communities in Korea. The 2022 ICTP-KIAS School on Statistical Physics for Life Sciences aims to introduce the next generation of students and researchers to these important themes: the quantitative understanding of life sciences, machine learning, and data science from the perspective of modern statistical physics. In addition to the pedagogical lectures, the school includes a small workshop for sharing recent research progresses among scientists at the frontier of this field. The school aims at providing unique opportunities for (junior) scientists in the Asia Pacific region to learn modern statistical physics and its applications to quantitative life science, machine learning, and data science. The 2022 ICTP-KIAS School will contribute to the cross-fertilization between physics and biology as well as to long-term scientific collaborations between researchers in Asia and ICTP scientists. Topics Information theory, machine learning and statistical physics Statistical mechanics of machine learning Information theory and criticality Statistical mechanics and reasoning Out-of-equilibrium statistical physics and life Biochemical rhythms and thermodynamics Non-equilibrium thermodynamics Information thermodynamics Stochastic thermodynamics Lecturers for the School:   Vipul Periwal (National Institutes of Health) Jae Sung Lee (Korea Institute for Advance Study) Pankaj Mehta (Boston University) Takahiro Sagawa (University of Tokyo) Speakers for the workshop:   Changbong Hyeon (Korea Institute for Advance Study) Hyunggyu Park (Korea Institute for Advance Study) Yongjoo Baek (Seoul National University) Tetsuya Kobayashi (University of Tokyo) Jae-Hyung Jeon (Pohang University of Science and Technology) Yong Woon Kim (Korea Advanced Institute of Science and Technology) Kunihiko Kaneko (Niels Bohr Institute) Antonio Celani (The Abdus Salam International Centre for Theoretical Physics) Vipul Periwal (National Institutes of Health) Deok-Sun Lee (Korea Institute for Advance Study) Junghyo Jo (Seoul National University)     DEADLINE to submit applications: 30 SEPTEMBER, 2022     Seoul - Republic of Korea ICTP pio@ictp.it 31 Oct 2022 - 8 Nov 2022

Europe/Rome 2022-12-05 07:00:00 2022-12-16 21:00:00 ICTP-ICTS Winter School on Quantitative Systems Biology | (smr 3755) An ICTP Hybrid Meeting. You can submit your application for participation in presence or online. Machine Learning is increasingly being used in biology, as also in other physical and life sciences, to build predictive models of underlying processes. This school will combine the knowledge of biologists who work with large and heterogeneous data, of physicists who are experts at modelling such complexity, and of machine learning experts who bring in state-of-the-art methods in statistics. This integrated approach is essential to learn how to tackle these issues and gain a better understanding of key phenomena in biology. Lecturers: P. CHAUDHARI, University of Pennsylvania, USA S. MUKHERJEE, MPG Leipzig, Germany E. PIASINI, SISSA, Italy G. SCHWEIKERT, University of Dundee, UK G. TKACIK, IST, Austria C. TOMASETTI, City of Hope, Los Angeles, USA C. VALLEJOS, University of Edinburgh, UK Scientific Advisory Committee: V. BALASUBRAMANIAN, University of Pennsylvania, USA A. CELANI, ICTP, Italy ​​S. JAIN, University of Delhi, India V.K. KRISHNAMURTHY, ICTS, Bangalore, India M. MARSILI, ICTP, Italy M. THATTAI, National Centre for Biological Sciences, India Grants: A limited number of grants are available to support the attendance of selected participants, with priority given to participants from developing countries. There is no registration fee. In person participation: As regards the COVID-19 policy, we advise to follow the updated rules available on the ICTP page Access Guidelines for Visitors. ICTP ICTP pio@ictp.it 5 Dec 2022 - 16 Dec 2022

Europe/Rome 2023-01-08 07:00:00 2023-01-27 21:00:00 Latin American Summer School in Computational Neuroscience – LACONEU 2023 | (smr 3813) The principal aim of LACONEU is to promote in Latin America the field of Computational Neuroscience through mathematical and computational tools and their applications in Biomedical Research and Artificial Intelligence. In LACONEU 2023 we expect to contribute to the development of the great potential, not always well exploited, that Latin America has in the field of numerical sciences: physics, engineering and mathematics. Along LACONEU 2023, we will encourage and motivate young graduate students and researchers to initiate interdisciplinary work on bioengineering and related problems. We will also encourage the creation of regional and international networks of collaborations reflected in joint research projects and theses. Topics: Network dynamics Learning in biological and artificial neural networks Knowledge representation Speakers: J. CRUZAT, LatBrain, Universidad Adolfo Ibañez, Chile S. DURA-BERNAL, State University of New York, USA P. GUEVARA, Universidad de Concepción, Chile C. SAVIN, NYU, USA E. TAGLIAZUCCHI, Universidad de Buenos Aires, Argentina A. TREVES, ICTP, Italy Grants: A limited number of grants are available to support the attendance of selected participants, with priority given to participants from developing countries. There is no registration fee. Valparaiso - Chile ICTP pio@ictp.it 8 Jan 2023 - 27 Jan 2023

Europe/Rome 2023-02-20 07:00:00 2023-03-17 21:00:00 Spring College in the Physics of Complex Systems | (smr 3817) ICTP ICTP pio@ictp.it 20 Feb 2023 - 17 Mar 2023