Complex Systems Studies

New paper studying the effect of travel restrictions on the spread of 2019-nCoV (COVID-19) is out on medrxiv. https://t.co/M3eotEdUX4

The Conference on Complex Systems (CCS) is the biggest and most important annual meeting of the international complex systems community. It comes under the auspices of the Complex Systems Society. This edition, after successful events in Singapore , Thessaloniki (Greece) , Cancun (Mexico) and Amsterdam (Netherlands), will take place in the Mediterranean island of Mallorca, Spain, organized by IFISC (CSIC-UIB). https://ccs2020.org/

مهلت فرستادن مقاله به یازدهمین کنفرانس فیزیک آماری، ماده چگال نرم و سیستم‌های پیچیده تا ۳۰ بهمن‌ماه تمدید شد. ✅ به کانال خبرى انجمن فیزیک ايران بپيوندید: 👇👇🏽👇👇🏽👇👇🏽👇 http://t.me/psinews

ریاضیات مالی: https://ocw.mit.edu/courses/mathematics/18-s096-topics-in-mathematics-with-applications-in-finance-fall-2013/index.htm

Statistical Mechanics and Emergent Phenomena in Biology More detailed information can be found on the school webpage: http://ipht.cea.fr/begrohu The deadline for application is the 31st of March.

✅ What is the power‐law distribution? https://rss.onlinelibrary.wiley.com/doi/full/10.1111/j.1740-9713.2017.01050.x%4010.1111/%28ISSN%291740-9713.TOP_SIGN_RESEARCH

🇮🇹 ICTP is now accepting applications for the Diploma Program for the academic year 2020-2021! Apply in Mathematics, Condensed Matter Physics, High Energy Physics, Earth System Physics, and Quantitative Life Sciences. Deadline: 29 February 2020. https://diploma.ictp.it/ http://ictp.it/c2vqd Quantitative Life Sciences The QLS Diploma programme is aimed at providing students with a quantitative and theoretical background that can allow them to access postgraduate programmes in a broad range of disciplines, including biophysics, quantitative biology and neuroscience, theoretical systems ecology, economics, data science, and machine learning. The diploma is organized along five main courses, on: Probability and Information Theory Quantitative Biology Neuroscience Ecology and Evolution Machine Learning and Artificial Intelligence Each are aimed at giving a core theoretical background for analyzing and modeling different phenomena in life sciences. These are complemented with shorter topical and advanced courses, seminars and journal clubs.

🔖 کنفرانس علوم اعصاب و فیزیک سامانه‌های نورونی 📒 ۳۰ بهمن‌ماه و ۱ اسفندماه 🏢 دانشکده فیزیک دانشگاه صنعتی شریف 📌 مهلت ثبت‌نام: ۱۵ بهمن‌ماه ✏️ اطلاعات بیشتر و ثبت‌نام: psi.ir/?neurophysics98 📍 @Neuro_Seminar 🆔 @Zharfa90

🎞 Salam Distinguished Lectures 2020 by Prof. Marc Mézard. Lecture 1: Artificial Intelligence: success, limits, myths and threats https://www.youtube.com/watch?v=oSUnILjIZJY Lecture 2: The spin glass cornucopia https://www.youtube.com/watch?v=w0Gl81jeqHg Lecture 3: Statistical physics of inference and machine learning https://www.youtube.com/watch?v=cqWYS3TXDUk

There are several maps of the current extent of the #nCoV2019 outbreak but if you are interested in a map of the public discussion taking place on Twitter about #nCov2019 then you should take a look at https://t.co/xcVlaoteOW

🎯 http://journals.aps.org/rmp/abstract/10.1103/RevModPhys.87.925

📽 Epidemics, Erdös Numbers and the Internet: the Physics of Networks https://podcasts.ox.ac.uk/epidemics-erd-s-numbers-and-internet-physics-networks 🌀 Physics Colloquium 12th February 2016 delivered by Professor Mark Newman Many systems of interest in science and engineering can be represented as networks: the internet, the power grid, transport networks, metabolic networks, ecological networks and social networks are just a few of the many well studied examples. The structure of these networks has deep implications for the behaviour of the systems they represent (for traffic flow on the internet, for instance, or the spread of a disease over a human social network). Their structure is complex and we need new tools to help make sense of it. Physics, perhaps surprisingly, has proved a rich source of such tools. This talk will introduce some of the fundamental ideas in this growing field. It will also demonstrate how techniques borrowed from quantum and statistical physics are helping us to understand a wide range of networked systems.