🎞 Asymptotics and perturbation methods
https://www.youtube.com/watch?v=KZsk8B_z8pI&feature=youtu.be
This is the introductory lecture in an applied math course on asymptotics and perturbation methods, offered by Prof. Steven Strogatz at Cornell University in Spring 2021.
Asymptotic methods and perturbation theory are clever techniques for finding approximate analytical solutions to complicated problems, by exploiting the presence of a large or small parameter. This course is an introduction to such methods and their applications in various branches of science and engineering.
The prerequisites are a knowledge of basic calculus and differential equations at an undergraduate level. The course emphasizes concrete examples, intuition, and applications to science and engineering, rather than theorems, proofs, and mathematical rigor. The treatment is friendly yet careful.
Topics include asymptotic expansion of integrals via Laplace's method, stationary phase, steepest descent, and saddle points. Perturbation methods for differential equations include dominant balance, boundary layer theory, multiple scales, and WKB theory. Most of the examples in the course deal with integrals or ordinary differential equations, but if time permits, we might also discuss some applications involving partial differential equations and difference equations.
https://www.youtube.com/watch?v=KZsk8B_z8pI&feature=youtu.be
This is the introductory lecture in an applied math course on asymptotics and perturbation methods, offered by Prof. Steven Strogatz at Cornell University in Spring 2021.
Asymptotic methods and perturbation theory are clever techniques for finding approximate analytical solutions to complicated problems, by exploiting the presence of a large or small parameter. This course is an introduction to such methods and their applications in various branches of science and engineering.
The prerequisites are a knowledge of basic calculus and differential equations at an undergraduate level. The course emphasizes concrete examples, intuition, and applications to science and engineering, rather than theorems, proofs, and mathematical rigor. The treatment is friendly yet careful.
Topics include asymptotic expansion of integrals via Laplace's method, stationary phase, steepest descent, and saddle points. Perturbation methods for differential equations include dominant balance, boundary layer theory, multiple scales, and WKB theory. Most of the examples in the course deal with integrals or ordinary differential equations, but if time permits, we might also discuss some applications involving partial differential equations and difference equations.
YouTube
Asymptotics and perturbation methods - Lecture 1: Asymptotic expansions
This is the introductory lecture in an applied math course on asymptotics and perturbation methods, offered by Prof. Steven Strogatz at Cornell University in Spring 2021.
Asymptotic methods and perturbation theory are clever techniques for finding approximate…
Asymptotic methods and perturbation theory are clever techniques for finding approximate…
📺 AMS Josiah Willard Gibbs Lecture on "What physics teaches us about computation in high dimensions"
https://t.co/aDr0SxQYkb
https://t.co/aDr0SxQYkb
YouTube
Lenka Zdeborová, "What physics teaches us about computation in high dimensions"
Lenka Zdeborová, École Polytechnique Fédérale de Lausanne, gives the AMS Josiah Willard Gibbs Lecture on "What physics teaches us about computation in high dimensions" on January 6, 2021 at the Joint Mathematics Meetings
💰 #PhD Call: Combat Disinformation in Complex Social Systems
https://www.michelecoscia.com/?p=1950
You want to work on the “Modelling Complex Social Systems to Handle Disinformation”?
The IT University of Copenhagen has put out a call searching for people interested in starting a PhD in computer science in Fall 2021. One of the projects you could work on is my project on disinformation and social networks. You should apply if you think you: might be interested in pursuing a PhD related to misinformation and social media; like the idea of living in the happiest country in the world; and are ok with having a clueless supervisor like me. Link to apply.
https://www.michelecoscia.com/?p=1950
You want to work on the “Modelling Complex Social Systems to Handle Disinformation”?
The IT University of Copenhagen has put out a call searching for people interested in starting a PhD in computer science in Fall 2021. One of the projects you could work on is my project on disinformation and social networks. You should apply if you think you: might be interested in pursuing a PhD related to misinformation and social media; like the idea of living in the happiest country in the world; and are ok with having a clueless supervisor like me. Link to apply.
HR Manager Talent Solutions
PhD Open Call 2021
What makes a person with COVID more contagious? Hint: not a cough
The amount of SARS-CoV-2 in a person’s body is a major factor in determining whether they are likely to transmit the virus to others, according to a study of nearly 300 infected people and their close contacts.
Most people with COVID-19 do not give it to anyone else, but some become ‘superspreaders’. To understand why, Michael Marks at the London School of Hygiene & Tropical Medicine and his colleagues monitored 282 people, deemed ‘index cases’, who had recently developed mild symptoms of COVID-19. The team also monitored 753 people who lived with, cared for or otherwise had close contact with the index cases (M. Marks et al. Lancet Infect. Dis. https://doi.org/10.1016/S1473-3099(20)30985-3; 2021).
Only one-third of the index cases transmitted the virus to a close contact. Those with a relatively high ‘viral load’, a measure of the amount of virus in the body, were much more likely to pass on the virus than were those with a low viral load. Index cases were no more likely to transmit the virus if they had a cough than if they didn’t.
The findings suggest that tracing the contacts of people with high viral loads is especially important, the authors say.
The amount of SARS-CoV-2 in a person’s body is a major factor in determining whether they are likely to transmit the virus to others, according to a study of nearly 300 infected people and their close contacts.
Most people with COVID-19 do not give it to anyone else, but some become ‘superspreaders’. To understand why, Michael Marks at the London School of Hygiene & Tropical Medicine and his colleagues monitored 282 people, deemed ‘index cases’, who had recently developed mild symptoms of COVID-19. The team also monitored 753 people who lived with, cared for or otherwise had close contact with the index cases (M. Marks et al. Lancet Infect. Dis. https://doi.org/10.1016/S1473-3099(20)30985-3; 2021).
Only one-third of the index cases transmitted the virus to a close contact. Those with a relatively high ‘viral load’, a measure of the amount of virus in the body, were much more likely to pass on the virus than were those with a low viral load. Index cases were no more likely to transmit the virus if they had a cough than if they didn’t.
The findings suggest that tracing the contacts of people with high viral loads is especially important, the authors say.
Sciencedirect
Transmission of COVID-19 in 282 clusters in Catalonia, Spain: a cohort study
Scarce data are available on what variables affect the risk of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the devel…
Brain & Mind Computational Seminar
23.2.2021 11:30 – 12:45 (Tehran Time)
A monthly seminar and venue for informal conversation about topics such as artificial intelligence, neuroscience, human behaviour, and digital humanities. Welcome!
Speakers:
Luigi Acerbi
Probabilistic machine and biological learning under resource constraints
Yasser Roudi
https://www.aalto.fi/en/events/brain-mind-computational-seminar
23.2.2021 11:30 – 12:45 (Tehran Time)
A monthly seminar and venue for informal conversation about topics such as artificial intelligence, neuroscience, human behaviour, and digital humanities. Welcome!
Speakers:
Luigi Acerbi
Probabilistic machine and biological learning under resource constraints
Yasser Roudi
https://www.aalto.fi/en/events/brain-mind-computational-seminar
Forwarded from Ali
دفاع از پایان نامه کارشناسی ارشد
گرایش فیزیک آماری و سامانه های پیچیده
عنوان:
روش یادگیری ماشین برای تعیین گذار فاز در پدیده های بحرانی
سخنران:
علی حقیقت گو
اساتید راهنما:
دکتر سید محمدصادق موحد
دکتر نیما خسروی
زمان: سه شنبه ۲۸ بهمن ساعت ۱۳:۰۰
لینک شرکت در جلسه مجازی:
http://194.225.24.96/defa-physics-1
همچنین با اسکن qr code موجود در تصویر میتوانید لینک را دریافت کنید.
از طریق نرم افزار adobe connect میتوانید در این جلسه حضور یابید.
adobe connect_windows
adobe connect_mac
adobe connect_android
با نصب نرم افزار و کپی کردن آدرس جلسه مجازی در نرم افزار میتوانید بصورت مهمان وارد جلسه شوید.
گرایش فیزیک آماری و سامانه های پیچیده
عنوان:
روش یادگیری ماشین برای تعیین گذار فاز در پدیده های بحرانی
سخنران:
علی حقیقت گو
اساتید راهنما:
دکتر سید محمدصادق موحد
دکتر نیما خسروی
زمان: سه شنبه ۲۸ بهمن ساعت ۱۳:۰۰
لینک شرکت در جلسه مجازی:
http://194.225.24.96/defa-physics-1
همچنین با اسکن qr code موجود در تصویر میتوانید لینک را دریافت کنید.
از طریق نرم افزار adobe connect میتوانید در این جلسه حضور یابید.
adobe connect_windows
adobe connect_mac
adobe connect_android
با نصب نرم افزار و کپی کردن آدرس جلسه مجازی در نرم افزار میتوانید بصورت مهمان وارد جلسه شوید.
💰 Doctor of Philosophy in Network Science
Application deadline is February 28, 2021. Please note that this is later than the general CEU application deadline. Anyone applying to our #PhD program before or on Feb 28 (until 23:59 CET) will be automatically considered for a scholarship.
We offer one of the most generous and accessible scholarship schemes, available to candidates from any country ranging from tuition awards to stipends.
Program Denoscription
The PhD program in Network Science is a research-oriented program that provides the only PhD degree in this field in Europe. Network science provides essential tools to study complex systems including society online and offline, the economy or urban traffic. Accordingly, the program provides hands-on experience with large datasets characterizing those systems and the skills needed to analyze them. At the same time, network science is a rapidly developing new discipline with ample opportunities to do fundamental research. Within the PhD program there are possibilities to carry out research either in applied or in theoretical-methodological directions.
The PhD program is open for students with a wide variety of backgrounds. Presently we have students with MA/MSc in math, physics, sociology, psychology, architecture, economics and political science. The Program is strongly interdisciplinary with a special emphasis on quantitative methods and data-oriented research. Those who have weaker math backgrounds will have to participate in a pre-session course and will need some additional effort.
⛳️ We do NOT request a GRE test.
https://networkdatascience.ceu.edu/phd-program-network-science-ceu
Application deadline is February 28, 2021. Please note that this is later than the general CEU application deadline. Anyone applying to our #PhD program before or on Feb 28 (until 23:59 CET) will be automatically considered for a scholarship.
We offer one of the most generous and accessible scholarship schemes, available to candidates from any country ranging from tuition awards to stipends.
Program Denoscription
The PhD program in Network Science is a research-oriented program that provides the only PhD degree in this field in Europe. Network science provides essential tools to study complex systems including society online and offline, the economy or urban traffic. Accordingly, the program provides hands-on experience with large datasets characterizing those systems and the skills needed to analyze them. At the same time, network science is a rapidly developing new discipline with ample opportunities to do fundamental research. Within the PhD program there are possibilities to carry out research either in applied or in theoretical-methodological directions.
The PhD program is open for students with a wide variety of backgrounds. Presently we have students with MA/MSc in math, physics, sociology, psychology, architecture, economics and political science. The Program is strongly interdisciplinary with a special emphasis on quantitative methods and data-oriented research. Those who have weaker math backgrounds will have to participate in a pre-session course and will need some additional effort.
⛳️ We do NOT request a GRE test.
https://networkdatascience.ceu.edu/phd-program-network-science-ceu
💰 Associate professor position (tenured) on Foundations of Data Science in KTH Royal Institute of Technology.
More details and online application: https://t.co/qxbxoiEsdk
Deadline April 15, 2021.
#DataScience
More details and online application: https://t.co/qxbxoiEsdk
Deadline April 15, 2021.
#DataScience
KTH
Associate Professor, Computer Science Spec. in Foundations of Data Science
På KTH blir du en del av en verksamhet som har en lång tradition av ledande forskning och utbildning. Hos oss får du möjlighet att ge liv åt dina idéer och samtidigt bidra till morgondagens samhälle.
"Applicability of Random Matrix Theory in Deep Learning" (by Nicholas P Baskerville, Diego Granziol, Jonathan P Keating):
https://t.co/fB7GD12Ujw
https://t.co/fB7GD12Ujw
Learn the basics of social network analysis in this free webinar at @UCONNmhealth:
Introduction to Social Network Analysis in mHealth and Social Media Research
Tues, Feb 23 at 11am ET
Register: https://t.co/hxqlq4SMa2
Introduction to Social Network Analysis in mHealth and Social Media Research
Tues, Feb 23 at 11am ET
Register: https://t.co/hxqlq4SMa2
Forwarded from Complex Networks (SBU)
💰 Hey, I am hiring at UCNZ UCNZMaths
• 1 fully paid, 3 years, #PhD scholarship
• a bunch of Research Assistant positions
Us: Data Science analysis of Social Networks with a strong Social Justice focus (yes, we're SJW).
You: curious, willing to learn transdisciplinary.
Our research methodology is maths, data and code heavy: hashtag #complexnetworks #DeepLearning #julialang. We also dialogue a lot with other disciplines and take ethics seriously.
The PhD is your adventure: you don't need to know everything in advance; can mix and match.
https://www.gvdallariva.net/
• 1 fully paid, 3 years, #PhD scholarship
• a bunch of Research Assistant positions
Us: Data Science analysis of Social Networks with a strong Social Justice focus (yes, we're SJW).
You: curious, willing to learn transdisciplinary.
Our research methodology is maths, data and code heavy: hashtag #complexnetworks #DeepLearning #julialang. We also dialogue a lot with other disciplines and take ethics seriously.
The PhD is your adventure: you don't need to know everything in advance; can mix and match.
https://www.gvdallariva.net/
www.gvdallariva.net
gvdrism
Giulio Valentino Dalla Riva Data Science UC
💉 What does 95% vaccine efficacy really mean?
Important, frequent misconception addressed here:
https://t.co/hS4syhoFZP
Important, frequent misconception addressed here:
https://t.co/hS4syhoFZP
APPLY | Applications for the Summer Institute in Computational Social Science @Princeton led by @msalganik and @chris_bail are due Feb 22. Institutes will also be held at 19 partner locations organized by SICSS alumni & the broader SICSS community.
https://t.co/QeU99khg7y
https://t.co/QeU99khg7y
Ten simple rules for navigating the computational aspect of an interdisciplinary PhD
https://t.co/yLKnCoHAsu
https://t.co/yLKnCoHAsu
journals.plos.org
Ten simple rules for navigating the computational aspect of an interdisciplinary PhD
Brain & Mind Computational Seminar
Luigi Acerbi & Yasser Roudi
23rd February 11:30 (Tehran Time):
Join us on Zoom here!
Luigi Acerbi
Probabilistic machine and biological learning under resource constraints
Yasser Roudi
Artificial Intelligence may beat us in chess, but not in memory
https://www.aalto.fi/en/events/brain-mind-computational-seminar
Luigi Acerbi & Yasser Roudi
23rd February 11:30 (Tehran Time):
Join us on Zoom here!
Luigi Acerbi
Probabilistic machine and biological learning under resource constraints
Yasser Roudi
Artificial Intelligence may beat us in chess, but not in memory
https://www.aalto.fi/en/events/brain-mind-computational-seminar
Can you speak Python?
Are you familiar with the Python programming language, along with the basic packages for scientific computing (NumPy/SciPy/Matplotlib/Pandas)?
To test your knowledge of these basics (and point you to relevant documentation to fill in any gaps), Aalto Scientific Computing team has designed the Gizmo challenge.
https://github.com/wmvanvliet/gizmo
Are you familiar with the Python programming language, along with the basic packages for scientific computing (NumPy/SciPy/Matplotlib/Pandas)?
To test your knowledge of these basics (and point you to relevant documentation to fill in any gaps), Aalto Scientific Computing team has designed the Gizmo challenge.
https://github.com/wmvanvliet/gizmo
GitHub
GitHub - wmvanvliet/gizmo: Python challenge
Python challenge. Contribute to wmvanvliet/gizmo development by creating an account on GitHub.