💡 Mongolia’s pandemic response has been so effective that nobody has died of covid-19 there, despite the long border with China. An epidemiologist there explains how the country has kept the virus at bay without a great public health system.

https://t.co/mMDFz05Psa

Computational Methods for Complex Systems
Instructor: Chris Myers

Computational science and engineering involves the synthesis of data structures, algorithms, numerical analysis, programming methodologies, simulation, visualization, data analysis, performance optimization, and use of emerging technologies, all applied to the study of complex problems in science and engineering. Physics 7682 is a graduate computational science laboratory course, emphasizing hands-on programming to address a number of interesting problems arising in physics, biology, engineering, applied mathematics, and computer science. The course is largely self-paced, allowing students to choose from among a variety of topics, and explore new problems of particular interest. Unlike other courses focused more specifically on algorithms, data structures or numerical analysis, this course emphasizes the integration of those and other topics to understand a variety of scientific phenomena and computational methods.

Computer Exercises

Topics
The course is organized around computational modules, which are drawn from a number of different fields. The course originally was a core element in the curriculum of Cornell's IGERT Program in Nonlinear Systems, which was organized broadly around the themes of complex networks, biolocomotion and manipulation, gene regulation, and pattern formation. Topics have evolved organically from that starting point. Modules are designed to expose students to techniques and methods from a variety of disciplines, not normally encompassed in a single course. Computational methods include solution of ordinary and partial differential equations, root finding, graph traversal, stochastic simulation via Monte Carlo, and various techniques in data analysis. Scientific topics include:

Complex networks, small worlds, and percolation
Human locomotion and models of walking
Dynamical systems, chaos, and iterated maps
Pattern formation and spiral waves in cardiac tissue
Chemical kinetics and gene regulatory networks
Random matrix theory
Random walks, extremal statistics, and stock fluctuations
Lattice Monte Carlo and the Ising model
Satisfiability and phase transitions in NP-complete problems
Molecular dynamics and the emergence of thermodynamics

https://pages.physics.cornell.edu/~myers/teaching/ComputationalMethods/index.html

👍 A gallery of interesting Jupyter Notebooks

This page is a curated collection of Jupyter/IPython notebooks that are notable. Feel free to add new content here, but please try to only include links to notebooks that include interesting visual or technical content; this should not simply be a dump of a Google search on every ipynb file out there.

https://github.com/jupyter/jupyter/wiki/A-gallery-of-interesting-Jupyter-Notebooks

خب سریع ایشان به فارسی ترجمه کرد :)
جدول ریسک انتقال بیماری - براساس این مقاله

Computational social science (CSS) has exploded in prominence over the past decade, with thousands of papers published using observational data, experimental designs, and large-scale simulations that were once unfeasible or unavailable to researchers.
https://t.co/tguwTFSChP

فیزیک حیرت‌آور ماسک‌های n95

ماسک‌های n95 یکی از موثرترین ماسک‌ها برای جلوگیری از عبور قطرات حامل ویروس #کرونا هستند. این ماسک‌ها با طراحی هوشمندانه‌ای سبب می‌شوند که ذرات با اندازه‌های مختلف از آن‌ها عبور نکنند؛ طراحی که پر است از نکته‌های فیزیکی! این شما و این ویدیو «فیزیک حیرت‌آور ماسک‌های n95» که توسط one minute physics ساخته شده. ویدیو زیرنویس فارسی دارد. برای دیدن نسخه‌های مختلف به لینک زیر سر بزنید:

🔗 sitpor.org/2020/08/n95masks/

🎞 @sitpor

Graph algorithms in the language of linear algebra

https://t.co/yjtE70cMVs

NeurIPS2020 workshop on 'Topological Data Analysis & Beyond' is open for submissions now:

https://t.co/4KhsCW0QXb

This is your chance to showcase work that combines #MachineLearning and #Topology.

Advice on giving Zoom talks

from David Tong @Cambridge_Uni
https://t.co/xclqEfsYR8

💡 https://petterhol.me/2020/09/01/common-mistakes-in-network-code/

The Biggest Ideas in the Universe | 23. Criticality and Complexity
https://www.aparat.com/v/X5nkF

"2020 SIAM Conference on Mathematics of Data Science: A Meeting Goes Virtual"

(by Gitta Kutyniok, Ali Pinar, and Joel A. Tropp; in ):

https://t.co/K8QZHZJiHq

💰 Interested in the physics of living matter and a highly interdisciplinary research environment? We have a number of open #postdoc positions. Details:

https://www.ds.mpg.de/3617867/job_full_offer_15201392

"From the Ising model to Kitaev Chain — An introduction to topological phase transitions" (by Kartik Chhajed):

https://t.co/aWXsE5B3fi

thoughts on notable developments in #neuroscience over the past decades:
https://t.co/V3EMWH2yg2

💰 #PhD positions in neuroscience! Fully-funded, interdisciplinary, Bachelor's or Master's students can apply! Either in Bonn, #Germany or in Jupiter, Florida (#USA). Join the International Max Planck Research School for Brain and Behavior!
Deadline: November 15
https://www.imprs-brain-behavior.org/admissions/application-info/

☀️ در اینجا سعی کرده‌ایم بر اساس هر شهری در ایران، اسامی اساتیدی که در حوزه سیستم‌های پیچیده فعال هستند را جمع آوری کنیم. این فهرست به شما کمک می‌کند تا در شهرهای مختلف گروه‌هایی که مشغول به پژوهش روی سیستم‌های پیچیده هستند را پیدا کنید.

💥 پیشنهاد ما به همه این است که در مقطع ارشد و دکتری، انتخاب دانشگاه بر اساس اساتید و گروه‌های پژوهشی مورد نظر شما باشد. برای همین، قبل از انتخاب دانشگاهی، توجه کنید که در آن دانشگاه با چه کس یا کسانی قرار است کار کنید. حتما با دانشجویان فارغ‌التحصیل از آن مراکز صحبت کنید! ظاهر و باطن انسان‌ها و گروه‌های پژوهشی گاهی بسیار متفاوت است.

💡 آیا باید دکتری بخوانم؟!

🔗 نوشته‌هایی برای ورود به گرایش فیزیک سیستم‌های پیچیده

با آرزوی موفقیت برای همه دانشجویان عزیز
امیدواریم که در این شرایط سخت، شور و اشتیاق علم در شما زنده مانده باشد.