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

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

A zoom lens for networks

Renormalization is a technique based on a repeated coarse-graining procedure used to study scale invariance and criticality in statistical physics. Now, an expansion of the renormalization toolbox allows to explore scale invariance in real-world networks.

https://www.nature.com/articles/s41567-022-01842-24

Check out our latest paper about our general purpose network library Reticula:
https://www.sciencedirect.com/science/article/pii/S2352711022002199

It natively supports (directed & undirected) (dyadic & hypergraph) (static & temporal) networks. C++ with Python bindings.

Install with pip on Python 3.8+:
$ python -m pip install -U reticula

Currently only supports Linux (glibc >= 2.17). Future windows + MacOS support is planned.

If this sounds interesting, do check out the documentation at reticula.network.

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

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.

"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

"On Composition and Complexity"

SFI Seminar by External Prof Marco Buongiorno Nardelli:
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

#Job: Assistant Professor in computational social science

https://vacatures.uva.nl/UvA/job/Core-Lecturer-Computational-Social-Science/756258802/

Economic Complexity - Theory and‌ Applications
NetSci Society Colloquium - Cesar Hidalgo

https://youtu.be/0IWlqwNzOV4

2022 wasn’t the year of Cleopatra – so why was she the most viewed page on Wikipedia?

https://theconversation.com/2022-wasnt-the-year-of-cleopatra-so-why-was-she-the-most-viewed-page-on-wikipedia-197350

Reddit is recruiting for Data Science interns for a range of projects ranging from ads to safety to community-building. Interns are being recruited from MS to PhD levels for summer roles, either in-person (SF or NYC) or remote. You can apply here: https://app.ripplematch.com/company/reddit/

#Postdoc research position on network epidemiology - livestock infections

We are looking for a post-doctoral researcher with expertise in network epidemiology to study the spread of livestock infections in France and in Europe. This work is part of an international collaboration.
https://iddjobs.org/jobs/post-doctoral-research-position-on-network-epidemiology-livestock-infections

Complex systems in the spotlight: next steps after the 2021 Nobel Prize in Physics

The 2021 Nobel Prize in Physics recognized the fundamental role of complex systems in the natural sciences. In order to celebrate this milestone, this editorial presents the point of view of the editorial board of JPhys Complexity on the achievements, challenges, and future prospects of the field. To distinguish the voice and the opinion of each editor, this editorial consists of a series of editor perspectives and reflections on few selected themes. A comprehensive and multi-faceted view of the field of complexity science emerges. We hope and trust that this open discussion will be of inspiration for future research on complex systems.

📎 https://iopscience.iop.org/article/10.1088/2632-072X/ac7f75

Thoughts on complex systems: an interview with Giorgio Parisi

The 2021 Nobel Prize in Physics was awarded 'for groundbreaking contributions to our understanding of complex physical systems', with half going to Giorgio Parisi 'for the discovery of the interplay of disorder and fluctuations in physical systems from atomic to planetary scales'. (The other half was jointly awarded to Syukuro Manabe and Klaus Hasselmann).

As part of this journal's wider celebration of the 2021 prize, JPhys Complexity Editor-in-Chief, Ginestra Bianconi, met with Nobel Laureate Giorgio Parisi to discuss his work on complex systems, his perspective on the wider field and advice for young researchers joining the community.

📎 https://iopscience.iop.org/article/10.1088/2632-072X/ac9171

Science in the age of selfies

A paper from PNAS describes what it takes to be a scientist today:
https://www.pnas.org/doi/10.1073/pnas.1609793113

Open #PhD position in #DataScience, #NetworkScience on clean, sustainable soils UTwente The Netherlands. Discover and validate links between species living in the soil with fresh data!
https://t.co/Ne7rEd731X

Deadline Mar 26

Wolfram|Alpha as the Way to Bring Computational Knowledge Superpowers to ChatGPT

https://writings.stephenwolfram.com/2023/01/wolframalpha-as-the-way-to-bring-computational-knowledge-superpowers-to-chatgpt/