The Enduring Mystery of How Water Freezes
Making ice requires more than subzero temperatures. The unpredictable process takes microscopic scaffolding, random jiggling and often a little bit of bacteria.
https://www.quantamagazine.org/the-enduring-mystery-of-how-water-freezes-20240617/
Making ice requires more than subzero temperatures. The unpredictable process takes microscopic scaffolding, random jiggling and often a little bit of bacteria.
https://www.quantamagazine.org/the-enduring-mystery-of-how-water-freezes-20240617/
Quanta Magazine
The Enduring Mystery of How Water Freezes | Quanta Magazine
Making ice requires more than subzero temperatures. The unpredictable process takes microscopic scaffolding, random jiggling and often a little bit of bacteria.
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Forwarded from Sitpor.org سیتپـــــور
YouTube
Science Communication in Network Science Community, Abbas K. Rizi
I’m a Network Epidemiologist who moonlights as a science writer for the public. I mainly contribute to science communication as the editor-in-chief of sitpor.org (FA). Using my experiences, both in science writing and as a TA of different courses, I will…
Science Communication in Network Science, Abbas K. Rizi
I’m a Network Epidemiologist who moonlights as a science writer for the public. I mainly contribute to science communication as the editor-in-chief of sitpor.org (FA). Using my experiences, both in science writing and as a TA of different courses, I will reflect on the situation of science communication in the network science community. I’ll discuss the opportunities and materials severely lacking at all levels, such as the educational material for grad students and laypeople.
🎞 https://youtu.be/R4IDFcCnTrk
----------------------------------------------
@sitpor | sitpor.org
instagram.com/sitpor_media
#سیتپـــــور به خاطر روایتگری در علم
I’m a Network Epidemiologist who moonlights as a science writer for the public. I mainly contribute to science communication as the editor-in-chief of sitpor.org (FA). Using my experiences, both in science writing and as a TA of different courses, I will reflect on the situation of science communication in the network science community. I’ll discuss the opportunities and materials severely lacking at all levels, such as the educational material for grad students and laypeople.
🎞 https://youtu.be/R4IDFcCnTrk
----------------------------------------------
@sitpor | sitpor.org
instagram.com/sitpor_media
#سیتپـــــور به خاطر روایتگری در علم
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📣 2024 Permanent Positions at IFISC!
Open call for two CSIC Tenured Scientist positions in "Cross-disciplinary Physics and Complex Systems" and "Theory of Quantum Technologies"
https://ifisc.uib-csic.es/en/about-ifisc/join-us/ifisc-new-permanent-researcher-positions/
Open call for two CSIC Tenured Scientist positions in "Cross-disciplinary Physics and Complex Systems" and "Theory of Quantum Technologies"
https://ifisc.uib-csic.es/en/about-ifisc/join-us/ifisc-new-permanent-researcher-positions/
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Media Complexity: Towards a Research Agenda to Study News Media Ecosystems
Djordje Padejski, Arizona State University
The talk will explore the applicability of complexity theory to journalism and mass communication studies in response to the digital transformation that has redefined journalistic practices, media narratives, and audience engagement. It will highlight the limitations of traditional research paradigms in capturing the complexity, nonlinearity, emergence, and interdependence of modern news media ecosystems. By integrating complexity theory, which focuses on adaptability, evolution, emergence, self-organization, and feedback mechanisms, among others, the talk intends to initiate a new research agenda. This includes examining the adaptability and evolution of media entities, the evolution of news narratives, the dynamics of media ecosystems, the diversity of media landscapes, self-organization in journalism, and the impact of audience feedback. The goal is to demonstrate the potential of complexity theory to offer novel insights into the evolving transformations in the journalism and mass communication field.
https://youtu.be/ionT6lXjFG4
Djordje Padejski, Arizona State University
The talk will explore the applicability of complexity theory to journalism and mass communication studies in response to the digital transformation that has redefined journalistic practices, media narratives, and audience engagement. It will highlight the limitations of traditional research paradigms in capturing the complexity, nonlinearity, emergence, and interdependence of modern news media ecosystems. By integrating complexity theory, which focuses on adaptability, evolution, emergence, self-organization, and feedback mechanisms, among others, the talk intends to initiate a new research agenda. This includes examining the adaptability and evolution of media entities, the evolution of news narratives, the dynamics of media ecosystems, the diversity of media landscapes, self-organization in journalism, and the impact of audience feedback. The goal is to demonstrate the potential of complexity theory to offer novel insights into the evolving transformations in the journalism and mass communication field.
https://youtu.be/ionT6lXjFG4
YouTube
Media Complexity: Towards a Research Agenda to Study News Media Ecosystems
Djordje Padejski, Arizona State University
The talk will explore the applicability of complexity theory to journalism and mass communication studies in response to the digital transformation that has redefined journalistic practices, media narratives, and…
The talk will explore the applicability of complexity theory to journalism and mass communication studies in response to the digital transformation that has redefined journalistic practices, media narratives, and…
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What Does Machine Learning Have to Offer Mathematics?
Jordan Ellenberg (University of Wisconsin–Madison)
Monday, July 22, 2024
5:30 – 7 p.m. PT
Simons Institute for the Theory of Computing
Calvin Lab auditorium
Please register to attend
The interaction of machine learning with math has attracted a lot of attention, because mathematics is in some respects a closed world with well-defined rules (like chess, and unlike poetry-writing) but also a domain where success is ultimately judged by human assessments of ingenuity and importance, not rigid criteria (like poetry-writing, and unlike chess). Can machines prove theorems? Can they have mathematical ideas? Jordan Ellenberg will talk about his joint work with researchers from DeepMind, which used novel techniques in machine learning to make progress in a problem in combinatorics, and will try to chart some near-term ways that machine learning may affect mathematical practice.
Jordan Ellenberg is a professor of mathematics at the University of Wisconsin–Madison specializing in number theory and arithmetic geometry, with additional interests in combinatorics, topology, and applications of machine learning to pure math. He is also the author of two general-audience books on mathematics, How Not to Be Wrong and Shape, as well as many articles in newspapers and magazines.
Jordan Ellenberg (University of Wisconsin–Madison)
Monday, July 22, 2024
5:30 – 7 p.m. PT
Simons Institute for the Theory of Computing
Calvin Lab auditorium
Please register to attend
The interaction of machine learning with math has attracted a lot of attention, because mathematics is in some respects a closed world with well-defined rules (like chess, and unlike poetry-writing) but also a domain where success is ultimately judged by human assessments of ingenuity and importance, not rigid criteria (like poetry-writing, and unlike chess). Can machines prove theorems? Can they have mathematical ideas? Jordan Ellenberg will talk about his joint work with researchers from DeepMind, which used novel techniques in machine learning to make progress in a problem in combinatorics, and will try to chart some near-term ways that machine learning may affect mathematical practice.
Jordan Ellenberg is a professor of mathematics at the University of Wisconsin–Madison specializing in number theory and arithmetic geometry, with additional interests in combinatorics, topology, and applications of machine learning to pure math. He is also the author of two general-audience books on mathematics, How Not to Be Wrong and Shape, as well as many articles in newspapers and magazines.
Simons Institute for the Theory of Computing
What Does Machine Learning Have to Offer Mathematics? | Theoretically Speaking
The interaction of machine learning with math has attracted a lot of attention, because mathematics is in some respects a closed world with well-defined rules (like chess, and unlike poetry-writing) but also a domain where success is ultimately judged by…
How America’s Fastest Swimmers Use Math to Win Gold?
Number theorist Ken Ono is teaching Olympians to swim more efficiently.
https://www.quantamagazine.org/how-americas-fastest-swimmers-use-math-to-win-gold-20240710/
Number theorist Ken Ono is teaching Olympians to swim more efficiently.
https://www.quantamagazine.org/how-americas-fastest-swimmers-use-math-to-win-gold-20240710/
Quanta Magazine
How America’s Fastest Swimmers Use Math to Win Gold
Number theorist Ken Ono is teaching Olympians to swim more efficiently.
JOW - What is Science Mix_v01 SEG A
How Is Science Even Possible?
How are scientists able to crack fundamental questions about nature and life? How does math make the complex cosmos understandable? In this episode, the physicist Nigel Goldenfeld and co-host Steven Strogatz explore the deep foundations of the scientific process.
https://www.quantamagazine.org/how-is-science-even-possible-20240620/
How are scientists able to crack fundamental questions about nature and life? How does math make the complex cosmos understandable? In this episode, the physicist Nigel Goldenfeld and co-host Steven Strogatz explore the deep foundations of the scientific process.
https://www.quantamagazine.org/how-is-science-even-possible-20240620/
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Course on Complexity Economics
Marco Pangallo’s course on Complexity Economics is part of the curriculum for the master’s degree in physics of complex systems at the University of Torino. The course aims to provide an interdisciplinary approach to understanding economic systems through the lens of complexity science. It covers basic methods and models used in complexity economics, focusing on the behavior and interactions of agents within economic systems. The course is designed to evolve into a comprehensive textbook on the subject, offering insights into non-mainstream, or heterodox, approaches to economics that leverage the tools and perspectives of complex systems science.
http://www.marcopangallo.it/blog/2024/06/25/my-course-on-complexity-economics/
Marco Pangallo’s course on Complexity Economics is part of the curriculum for the master’s degree in physics of complex systems at the University of Torino. The course aims to provide an interdisciplinary approach to understanding economic systems through the lens of complexity science. It covers basic methods and models used in complexity economics, focusing on the behavior and interactions of agents within economic systems. The course is designed to evolve into a comprehensive textbook on the subject, offering insights into non-mainstream, or heterodox, approaches to economics that leverage the tools and perspectives of complex systems science.
http://www.marcopangallo.it/blog/2024/06/25/my-course-on-complexity-economics/
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2 year #Postdoc position with the option of extension. Deadline for application is August 16.
The new Center for Synergy of Systems (SynoSys) develops transdisciplinary approaches and methods in the fields of network science, data science and citizen science in order to conduct integrative research into complex phenomena at the interfaces between biomedicine, social sciences and life sciences.
https://www.verw.tu-dresden.de/StellAus/stelle.asp?id=11538&lang=en
The new Center for Synergy of Systems (SynoSys) develops transdisciplinary approaches and methods in the fields of network science, data science and citizen science in order to conduct integrative research into complex phenomena at the interfaces between biomedicine, social sciences and life sciences.
https://www.verw.tu-dresden.de/StellAus/stelle.asp?id=11538&lang=en
www.verw.tu-dresden.de
Vacancy ID 11538
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I am looking for at least one #postdoc researcher with an initial appointment till March 2026, which may be extendable befond March 2026 (with a realistic probability). The work location is the State University of New York at Buffalo, Buffalo, NY, USA. The postdoc will be advised by Professor Naoki Masuda
and housed in the Department of Mathematics (while the research itself is more data analytic, bioinformatic, and/or computational, rather than mathematical).
The project has multiple subtopics, and priority areas are (i) gene network analysis and (ii) other (specific) biomedical data analysis related to network analysis (early warning, health behavior, etc.). The project is at intersection between network science and biology/biomedicine.
Experience in bioinformatics in broad terms, genome biology, network science, data science, time series analysis, or related fields, and good communication skills are desired.
If interested, please email to naokimas@gmail.com
and housed in the Department of Mathematics (while the research itself is more data analytic, bioinformatic, and/or computational, rather than mathematical).
The project has multiple subtopics, and priority areas are (i) gene network analysis and (ii) other (specific) biomedical data analysis related to network analysis (early warning, health behavior, etc.). The project is at intersection between network science and biology/biomedicine.
Experience in bioinformatics in broad terms, genome biology, network science, data science, time series analysis, or related fields, and good communication skills are desired.
If interested, please email to naokimas@gmail.com
#Postdoc position on the science of science available at Indiana University.
indiana.peopleadmin.com/postings/25173
indiana.peopleadmin.com/postings/25173
Peopleadmin
Post-doctoral Fellow (Science of Science)
The Luddy School of Informatics, Computing, and Engineering seeks a post-doctoral fellow in the area of science of science. Position is for 1 year with a possibility of an extension of an additional year.The successful candidate will work with Prof. Santo…
From Ronald Ross to ChatGPT: the birth and strange life of the random walk Jordan Ellenberg
https://youtu.be/08FGB5x090M?si=DFdtl3BrMvSddywL
Between 1905 and 1910 the idea of the random walk, now a major topic in applied maths, was invented simultaneously and independently by multiple people in multiple countries for completely different purposes – in the UK, the story starts with Ronald Ross and the problem of mosquito control, but elsewhere, the theory was being developed in domains from physics to finance to winning a theological argument (really!).
Jordan tells some part of this story and also gesture at ways that random walks (or Markov processes, named after the theological arguer) underlie current approaches to artificial intelligence; he touches on some of his own work with DeepMind and speculates about the capabilities of those systems now and in the future.
Jordan Ellenberg is a Professor of Mathematics at the University of Wisconsin-Madison.
https://youtu.be/08FGB5x090M?si=DFdtl3BrMvSddywL
Between 1905 and 1910 the idea of the random walk, now a major topic in applied maths, was invented simultaneously and independently by multiple people in multiple countries for completely different purposes – in the UK, the story starts with Ronald Ross and the problem of mosquito control, but elsewhere, the theory was being developed in domains from physics to finance to winning a theological argument (really!).
Jordan tells some part of this story and also gesture at ways that random walks (or Markov processes, named after the theological arguer) underlie current approaches to artificial intelligence; he touches on some of his own work with DeepMind and speculates about the capabilities of those systems now and in the future.
Jordan Ellenberg is a Professor of Mathematics at the University of Wisconsin-Madison.
YouTube
From Ronald Ross to ChatGPT: the birth and strange life of the random walk - Jordan Ellenberg
Between 1905 and 1910 the idea of the random walk, now a major topic in applied maths, was invented simultaneously and independently by multiple people in multiple countries for completely different purposes – in the UK, the story starts with Ronald Ross…
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#postdoc to develop an Agent-Based Model (#ABM) that simulates the socio-economic impacts of local transformation processes on the economy and population.
ℹ️ csh.ac.at/engage/jobs/
ℹ️ csh.ac.at/engage/jobs/
92 Tweets from a mathematical physicist on Entropy in form of a book:
http://math.ucr.edu/home/baez/what_is_entropy.pdf
http://math.ucr.edu/home/baez/what_is_entropy.pdf
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#PhD position in computational social science at TU Graz
https://jobs.tugraz.at/en/jobs/54e87f3a-36f8-a13a-b6ae-6577fa57cbfd
https://jobs.tugraz.at/en/jobs/54e87f3a-36f8-a13a-b6ae-6577fa57cbfd
Statistical Laws in Complex Systems
Eduardo G. Altmann
Statistical laws describe regular patterns observed in diverse scientific domains, ranging from the magnitude of earthquakes (Gutenberg-Richter law) and metabolic rates in organisms (Kleiber's law), to the frequency distribution of words in texts (Zipf's and Herdan-Heaps' laws), and productivity metrics of cities (urban scaling laws). The origins of these laws, their empirical validity, and the insights they provide into underlying systems have been subjects of scientific inquiry for centuries. This monograph provides an unifying approach to the study of statistical laws, critically evaluating their role in the theoretical understanding of complex systems and the different data-analysis methods used to evaluate them. Through a historical review and a unified analysis, we uncover that the persistent controversies on the validity of statistical laws are predominantly rooted not in novel empirical findings but in the discordance among data-analysis techniques, mechanistic models, and the interpretations of statistical laws. Starting with simple examples and progressing to more advanced time-series and statistical methods, this monograph and its accompanying repository provide comprehensive material for researchers interested in analyzing data, testing and comparing different laws, and interpreting results in both existing and new datasets.
https://arxiv.org/abs/2407.19874
Eduardo G. Altmann
Statistical laws describe regular patterns observed in diverse scientific domains, ranging from the magnitude of earthquakes (Gutenberg-Richter law) and metabolic rates in organisms (Kleiber's law), to the frequency distribution of words in texts (Zipf's and Herdan-Heaps' laws), and productivity metrics of cities (urban scaling laws). The origins of these laws, their empirical validity, and the insights they provide into underlying systems have been subjects of scientific inquiry for centuries. This monograph provides an unifying approach to the study of statistical laws, critically evaluating their role in the theoretical understanding of complex systems and the different data-analysis methods used to evaluate them. Through a historical review and a unified analysis, we uncover that the persistent controversies on the validity of statistical laws are predominantly rooted not in novel empirical findings but in the discordance among data-analysis techniques, mechanistic models, and the interpretations of statistical laws. Starting with simple examples and progressing to more advanced time-series and statistical methods, this monograph and its accompanying repository provide comprehensive material for researchers interested in analyzing data, testing and comparing different laws, and interpreting results in both existing and new datasets.
https://arxiv.org/abs/2407.19874
arXiv.org
Statistical Laws in Complex Systems
Statistical laws describe regular patterns observed in diverse scientific domains, ranging from the magnitude of earthquakes (Gutenberg-Richter law) and metabolic rates in organisms (Kleiber's...
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2025 Complexity #Postdoc Fellowships.
Complexity Fellows contribute to SFI’s research and collaborate with leading researchers worldwide.
If you’ve completed your PhD in any scientific discipline, and are interested in transdisciplinary research, consider this unique opportunity at the Santa Fe Institute.
Applications are open until October 11 – check out application requirements and benefits here:
https://apply-sfi.smapply.org/prog/complexity_postdoctoral_fellowship_/
Complexity Fellows contribute to SFI’s research and collaborate with leading researchers worldwide.
If you’ve completed your PhD in any scientific discipline, and are interested in transdisciplinary research, consider this unique opportunity at the Santa Fe Institute.
Applications are open until October 11 – check out application requirements and benefits here:
https://apply-sfi.smapply.org/prog/complexity_postdoctoral_fellowship_/
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In the process of building the new Center Synergy of Systems (SynoSys), (https://synosys.github.io) at Technische Universität Dresden we are looking for a data visualization specialist to develop interactive, web-based visualizations of our research. If you share our interest of anti-disciplinary research and bring the required skills, have a look at the job post and apply.
https://lnkd.in/e9Zh3F4g
https://lnkd.in/e9Zh3F4g
SynoSys
Center Synergy of Systems, Department of the Center of Interdisciplinary Digital Science (CIDS)
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Forwarded from Sitpor.org سیتپـــــور
Media is too big
VIEW IN TELEGRAM
A Deep Dive into Aalto ScienceIT Project:
An Interview with Richard Darst
🎞 Video on YouTube 🎧 Audio
Richard Darst from Aalto Science IT discusses the transition from chemistry to network science, emphasizing the importance of software engineering support & practical training for researchers. He explains the development and benefits of Aalto’s Triton HPC cluster and JupyterHub, and how his team assists researchers with essential computational tools and user-friendly training programs. A must-watch for anyone interested in scientific computing and interdisciplinary collaboration.
• The Aalto Research Software Engineers (RSEs)
• CodeRefinery Project
• Triton HPC Cluster
• Aalto Science IT Services
🔗 Don’t forget to like, comment, and subscribe for more: youtube.com/AbbasKRizi
----------------------------------------------
@sitpor | sitpor.org
instagram.com/sitpor_media
#سیتپـــــور به خاطر روایتگری در علم
An Interview with Richard Darst
🎞 Video on YouTube 🎧 Audio
Richard Darst from Aalto Science IT discusses the transition from chemistry to network science, emphasizing the importance of software engineering support & practical training for researchers. He explains the development and benefits of Aalto’s Triton HPC cluster and JupyterHub, and how his team assists researchers with essential computational tools and user-friendly training programs. A must-watch for anyone interested in scientific computing and interdisciplinary collaboration.
• The Aalto Research Software Engineers (RSEs)
• CodeRefinery Project
• Triton HPC Cluster
• Aalto Science IT Services
🔗 Don’t forget to like, comment, and subscribe for more: youtube.com/AbbasKRizi
----------------------------------------------
@sitpor | sitpor.org
instagram.com/sitpor_media
#سیتپـــــور به خاطر روایتگری در علم
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