Complex Systems Studies

Economic Complexity - Theory and‌ Applications NetSci Society Colloquium - Cesar Hidalgo https://youtu.be/0IWlqwNzOV4

#Job: Assistant Professor in computational social science https://vacatures.uva.nl/UvA/job/Core-Lecturer-Computational-Social-Science/756258802/

"On Composition and Complexity" SFI Seminar by External Prof Marco Buongiorno Nardelli, streaming now: https://youtube.com/watch?v=nQHnQ6HOebI #music #complexsystems "We can look at musical spaces — every kind of aspect of music, like harmony, melody, orchestration, timbre, rhythm — can be represented as networks." https://arxiv.org/abs/1905.01842

"The production and spread of scientific ideas" the science of science & how prestige shapes pretty much everything in academia, for the Data Science Research Centre at Caritas Inst. of Higher Ed. in HK https://youtu.be/cX2sXEMkKhw

Statistical Physics of Stochastic Populations and other #PhD positions https://ifisc.uib-csic.es/en/about-ifisc/join-us/doctoral-inphinit-fellowships-programme/ Deadline 25th Jan.

Do you want to come and work in Paris? We have 2 open post-doc positions in network epidemiology at the epicx lab, Pierre Louis Institute of Epidemiology and Public Health, Modeling and surveillance team. https://www.epicx-lab.com/open-positions.html

Modern computational studies of the glass transition The physics of the glass transition and amorphous materials continues to attract the attention of a wide research community after decades of effort. Supercooled liquids and glasses have been studied numerically since the advent of molecular dynamics and Monte Carlo simulations, and computer studies have greatly enhanced both experimental discoveries and theoretical developments. In this #Review, we provide a modern perspective on this area. We describe the need to go beyond canonical methods when studying the glass transition — a problem that is notoriously difficult in terms of timescales, length scales and physical observables. We summarize recent algorithmic developments to achieve enhanced sampling and faster equilibration by using replica-exchange methods, cluster and swap Monte Carlo algorithms, and other techniques. We then review some major advances afforded by these tools regarding the statistical mechanical description of the liquid-to-glass transition, and the mechanical, vibrational and thermal properties of the glassy solid. https://www.nature.com/articles/s42254-022-00548-x

Check out our latest paper about our general purpose network library Reticula: sciencedirect.com/science/articl… It natively supports (directed || undirected) (dyadic || hypergraph) (static || temporal) networks. C++ with Python bindings.

Laplacian renormalization group for heterogeneous networks Pablo Villegas, Tommaso Gili, Guido Caldarelli & Andrea Gabrielli The renormalization group is the cornerstone of the modern theory of universality and phase transitions and it is a powerful tool to scrutinize symmetries and organizational scales in dynamical systems. However, its application to complex networks has proven particularly challenging, owing to correlations between intertwined scales. To date, existing approaches have been based on hidden geometries hypotheses, which rely on the embedding of complex networks into underlying hidden metric spaces. Here we propose a Laplacian renormalization group diffusion-based picture for complex networks, which is able to identify proper spatiotemporal scales in heterogeneous networks. In analogy with real-space renormalization group procedures, we first introduce the concept of Kadanoff supernodes as block nodes across multiple scales, which helps to overcome detrimental small-world effects that are responsible for cross-scale correlations. We then rigorously define the momentum space procedure to progressively integrate out fast diffusion modes and generate coarse-grained graphs. We validate the method through application to several real-world networks, demonstrating its ability to perform network reduction keeping crucial properties of the systems intact. https://www.nature.com/articles/s41567-022-01866-8

Available #PhD positions at NTNU math department: PhD 1: [PDEs, SPDEs, mean field games, etc] + [neuro, stoch. control theory, etc] PhD 2: [Comp/spatial/Bayesian stats, SPDEs, etc] + [fluid mechanics] Deadline: 01/31/2023 https://www.jobbnorge.no/en/available-jobs/job/237922/2-phd-positions-in-the-project-imod-an-interdisciplinary-approach-to-data-based-modelling

When you cast a visible light shadow you also cast a thermal shadow. But while the former disappear when you walk away, an infrared thermography shows you the latter staying on the wall. [source: https://buff.ly/3RsB6r4]

Defining physicists’ relationship with AI As physicists are increasingly reliant on artificial intelligence (AI) methods in their research, we ponder the role of human beings in future scientific discoveries. Will we be guides to AI, or be guided by it? https://www.nature.com/articles/s42254-022-00544-1

اینجا کدهای کتاب An Introduction to Modeling Neuronal Dynamics, Christoph Börgers 2017 را به صورت یک پکیج پایتون پیاده سازی کردم که میشه کدها رو به صورت آنلاین و بدون نصب پکیجی و مستقل از سیستم عاملی که استفاده می کنید اجرا کرد. کتاب خوبی برای یادگیری هست. پکیج میتونه هنگام تدریس استفاده شود. ده فصل از کتاب آماده شده. باقی فصل ها به زودی اضافه می شود. https://github.com/Ziaeemehr/mndynamics/tree/main/mndynamics/examples

Up to 9 #PhD contracts will be offered soon IFISC mallorca, including one contract to work with me and Miguel Cornelles at the interface of complex systems and machine learning. Please spread the word !! Details here 👉 lnkd.in/dEPy6fNq

Sixth Groningen Spring School on Cognitive Modeling – ACT-R, Nengo, PRIMs – Date: 27-31 March 2023 Location: Groningen, the Netherlands Fee: € 305 (late fee after February 26 will be € 355) More information and registration: www.cognitive-modeling.com/springschool ____________________ Dear colleagues and students, We are excited to announce the sixth Spring School on Cognitive Modeling in Groningen, from 27-31 March 2023! This time, the Spring School will cover three different modeling paradigms: ACT-R, Nengo, and PRIMs. Each of these topics consists of a series of lectures, as well as a number of hands-on exercises (tutorials). Past years have shown that students get most out of the spring school if they really emerge themselves into one modeling paradigm. We therefore recommend you choose one topic for which you will attend both the lectures as well as the tutorials. In addition, you can select a second paradigm, for which you attend the lectures only. To give students a broader picture, there will also be three guest lectures throughout the week. These lectures each give an introduction to yet another modeling paradigm: accumulator models (Leendert van Maanen), error-driven learning models (Jacolien van Rij), and dynamical systems (Herbert Jäger). Everyone is encouraged to attend those lectures. To round of the program, there will be a poster session, where students present themselves and their research, as well as a city tour, and our (in)famous spring school dinner. Registration is now open. Please feel free to forward the information to anyone who might be interested in the Spring School. We are looking forward to welcoming you (again) in Groningen, The Spring School team springschool@rug.nl

A Mathematical Journey through Scales - Martin Hairer Oxford Mathematics Public Lecture The tiny world of particles and atoms and the gigantic world of the entire universe are separated by about forty orders of magnitude. As we move from one to the other, the laws of nature can behave in drastically different ways, sometimes obeying quantum physics, general relativity, or Newton’s classical mechanics, not to mention other intermediate theories. Understanding the transformations that take place from one scale to another is one of the great classical questions in mathematics and theoretical physics, one that still hasn't been fully resolved. In this lecture, we will explore how these questions still inform and motivate interesting problems in probability theory and why so-called toy models, despite their superficially playful character, can sometimes lead to certain quantitative predictions. Professor Martin Hairer is Professor of Pure Mathematics at Imperial College London. He was awarded the Fields Medal in 2014. https://youtu.be/TOY52LF_ZTA

For bread, think steering wheels. For custard, think toothpaste. Oxford Christmas Public Lecture Watch on Tuesday 20 December at 5pm and any time after: https://www.youtube.com/c/OxfordMathematics

I'm looking for a #PhD student who will work with me at VUamsterdam on mathematics and network science! The deadline is March 1st. Details on the position can be found at https://workingat.vu.nl/ad/phd-position-in-the-mathematics-of-network-science/g979oo

IFISC offers up to 7 #PhD positions within the Doctoral INPhINIT Fellowships Programme. The opportunity you are looking for! ifisc.uib-csic.es/en/about-ifisc… Deadline: 25/01/23