〽️ THE 2019 30 under 30 Inventing the future from the atom up
🌐 https://www.forbes.com/30-under-30/2019/science/#18aaf2477add
🎲 @ComplexSys
🌐 https://www.forbes.com/30-under-30/2019/science/#18aaf2477add
🎲 @ComplexSys
☄ We just launched our new browse page - all of the amazing, high-quality resources on Complexity Explorer can now be searched according to topic, type, difficulty, and/or source.
Here is a little bit about what each of these fields mean:
Topic: The Complexity Explorer Team decided these topics comprehensively represent Complex Systems Science and the content on Complexity Explorer.
Type: These are the eight content types we have on Complexity Explorer.
Difficulty Levels:
Level 1: Straightforward and easy-to-navigate descriptions requiring little to no mathematical calculations and are intended for an audience without an assumption of background. Articles, pop-sci books, educational videos, general blogs, course syllabi, etc. that take a short time commitment.
Level 2: Slightly technical material requiring some basic mathematics that may include basic calculus and algebra for full understanding. "Entry" level science—which can be applied or theoretical—and should be understandable by those with undergraduate math and science courses. These should take at most an evening's work to fully understand.
Level 3: Methods or tools that build off of an assumed knowledge base. A wide range of competency covered and may include the use of nonlinear differential equations and matrix algebra to illustrate concepts. Typically defined as "advanced undergraduate to early graduate." Time commitment varies, but these require some expertise in a subject area to fully comprehend.
Level 4: Technically advanced or field-specific topics that usually require an extensive background in the subject field to comprehend fully, while those outside the field may not understand techniques or references. Graduate-level material that requires a professional level of expertise in understanding or applications. Also reserved for Masters and PhD-level program descirption pages.
Source: This helps you know what or what type of institution or party is responsible for the production of this resource. For content we make in house - it is either Complexity Explorer or Santa Fe Institute. For content that you can access online - link an online course from someone else this would be 'Online'. For resources that are not courses, but something like an informative webpage, or a blog, we call those 'Web Resources'. Lastly, we like to acknowledge our fellow Complexity Research Centers, so you will see these centers there too!
You will also notice that we have now color coded each content type!
We hope you enjoy this new utility and, as this is a brand new functionality for Complexity Explorer, please let us know any feedback about how you like it or how to improve it at admin@complexityexplorer.org.
In the future we hope to make the curation and tagging of resources an interactive element for users to participate in - so stay tuned and thanks for all being Complexity Explorers!
Here is a little bit about what each of these fields mean:
Topic: The Complexity Explorer Team decided these topics comprehensively represent Complex Systems Science and the content on Complexity Explorer.
Type: These are the eight content types we have on Complexity Explorer.
Difficulty Levels:
Level 1: Straightforward and easy-to-navigate descriptions requiring little to no mathematical calculations and are intended for an audience without an assumption of background. Articles, pop-sci books, educational videos, general blogs, course syllabi, etc. that take a short time commitment.
Level 2: Slightly technical material requiring some basic mathematics that may include basic calculus and algebra for full understanding. "Entry" level science—which can be applied or theoretical—and should be understandable by those with undergraduate math and science courses. These should take at most an evening's work to fully understand.
Level 3: Methods or tools that build off of an assumed knowledge base. A wide range of competency covered and may include the use of nonlinear differential equations and matrix algebra to illustrate concepts. Typically defined as "advanced undergraduate to early graduate." Time commitment varies, but these require some expertise in a subject area to fully comprehend.
Level 4: Technically advanced or field-specific topics that usually require an extensive background in the subject field to comprehend fully, while those outside the field may not understand techniques or references. Graduate-level material that requires a professional level of expertise in understanding or applications. Also reserved for Masters and PhD-level program descirption pages.
Source: This helps you know what or what type of institution or party is responsible for the production of this resource. For content we make in house - it is either Complexity Explorer or Santa Fe Institute. For content that you can access online - link an online course from someone else this would be 'Online'. For resources that are not courses, but something like an informative webpage, or a blog, we call those 'Web Resources'. Lastly, we like to acknowledge our fellow Complexity Research Centers, so you will see these centers there too!
You will also notice that we have now color coded each content type!
We hope you enjoy this new utility and, as this is a brand new functionality for Complexity Explorer, please let us know any feedback about how you like it or how to improve it at admin@complexityexplorer.org.
In the future we hope to make the curation and tagging of resources an interactive element for users to participate in - so stay tuned and thanks for all being Complexity Explorers!
👨🏫 Winter School, "Physics and Mathematics of Turbulent Flows at Different Scales", February 24 – March 1, 2019 at the Les Houches Physics center in Les Houches, France.
https://t.co/4vVJODgVSh
The deadline for applications is January 15, 2019.
https://t.co/4vVJODgVSh
The deadline for applications is January 15, 2019.
Le Laboratoire des Sciences du Climat et de l'Environnement
Extrèmes : Statistiques, Impacts et Régionalisation
L’équipe ESTIMR a pour objectifs principaux : la compréhension et la modélisation de la variabilité climatique et environnementale à différentes échelles spatiales – depuis les très grandes structures liées à la dynamique atmosphérique jusqu’à des phénomènes…
🏦 We are happy to announce that the Scholarships for Events on Complex Systems (SECS) and Bridge Grants are back. They are both dedicated to young researchers from Complex Systems Society, who need funds to attend complex systems related events or want to start an international project with other young scientist. More information at:
yrcss.cssociety.org/secs/
and
yrcss.cssociety.org/bridge-grants/
yrcss.cssociety.org/secs/
and
yrcss.cssociety.org/bridge-grants/
yrcss.cssociety.org
SECS
Scholarships for Events on Complex Systems (SECS)The yrCSS wants to encourage young scientists to participate in complex systems events. SECS are conceived for this very purpose. Scholarship for Even
〽️New web home for the Global Epidemic and Mobility Project- GLEAM.
🌐 https://www.gleamproject.org
🎲 @ComplexSys
🌐 https://www.gleamproject.org
🎲 @ComplexSys
Forwarded from ترجمان علوم انسانى
🎯 در خیابانهای توییتر حقیقت مثل یک ماشین قراضه است و اخبار جعلی شبیه ماشینی آخرین مدل. طبیعی است که ماشینهای آخرین مدل سریعتر از «ماشین قراضه» خیابانهای توییتر را بالا و پایین میکنند و توجه بیشتری جلب میکنند. طبق یافتههای علمی دروغ شش برابر سریعتر از حقیقت در توییتر بازنشر میشود. این شرایط تقصیر کیست و برایش چه میتوان کرد؟
🎧 ادامۀ مطلب را در لینک زیر بشنوید:
tarjomaan.com/sound/9192/
📌 نوشتار این مطلب را اینجا بخوانید:
tarjomaan.com/neveshtar/8998/
🔗 @tarjomaanweb
🎧 ادامۀ مطلب را در لینک زیر بشنوید:
tarjomaan.com/sound/9192/
📌 نوشتار این مطلب را اینجا بخوانید:
tarjomaan.com/neveshtar/8998/
🔗 @tarjomaanweb
💲 MSR Postdoctoral Researcher - Computational Social Sciences https://t.co/RDKOnniwjC
Microsoft
Postdoctoral Researcher - Computational Social Sciences in New York, New York, United States | Research at Microsoft
Apply for Postdoctoral Researcher - Computational Social Sciences job with Microsoft in New York, New York, United States. Research at Microsoft
#سمینارهای_هفتگی مرکز شبکههای پیچیده و مردمشناسی دانشگاه شهید بهشتی
⏰ یکشنبه، ۲۷ آبان، ساعت ۱۶:۴۵
🏛 محل برگزاری: سالن ابن هیثم
@mhakim
⏰ یکشنبه، ۲۷ آبان، ساعت ۱۶:۴۵
🏛 محل برگزاری: سالن ابن هیثم
@mhakim
🎞 Physicist Michelle Girvan's Community Lecture on "reservoir computing," which uses chaos to teach machine learning systems to better predict chaotic systems like weather, markets, and brain activity:
https://www.youtube.com/watch?v=MLNtHK0-DEw&feature=youtu.be
https://www.youtube.com/watch?v=MLNtHK0-DEw&feature=youtu.be
YouTube
SFI Community Lecture - Michelle Girvan
Harnessing Chaos and Predicting the Unpredictable with Artificial Intelligence In recent years, machine learning methods such as "deep learning" have proven ...
🎞 Applying Complexity Science to Building The Blockchain Economy, a talk at NTU Singapore by Joss Colchester
https://t.co/UFJWwWCqxB
https://t.co/UFJWwWCqxB
YouTube
Applying Complexity Science to Building The Blockchain Economy A Presentation
In this presentation given at NTU Innovation Centre Singapore Joss Colchester illustrates how are economic systems of organization are rapidly shifting towar...
IOP members: we provide financial support to research students and early career researchers to attend international meetings and international facilities. Don't miss out! Visit https://t.co/G8uaAk3F9Z to find out more and apply online by 1 December! #IOPTravelBursaries https://t.co/WuH93IhMXd