Complex Systems Studies
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What's up in Complexity Science?!
Check out here:

@ComplexSys

#complexity #complex_systems #networks #network_science

πŸ“¨ Contact us: @carimi
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Mathematical Methods in Computational Neuroscience Summer Camp

10-28/July
in lovely Norway (amazing/middle of nowhere). No tuition and room/board/food(good) is covered. Great experience/speakers/students/activities!

https://compneuronrsn.org
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The program of the "Lectures on Computational Linguistics 2023" is out! The event will be held in Pisa, 29th-31st May 2023.
Participation is free but subject to registration:
https://www.ai-lc.it/lectures/lectures-2023-it/
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Registration open for the "School of the Italian Society of Statistical Physics" (second edition).
When? August 28 - September 7, 2023
Where? IMT School for Advanced Studies, Lucca,Italy

https://sifsschool2023.imtlucca.it/
#PhD Studentship in Social Statistics University of Manchester &
Max Planck Institute for Demographic Research (MPIDR)
Deadline: 14th of May 2023

https://t.co/UwTf4Z7X05
want to delve into Computational Biology & #Bioinformatics for your #Master's? Apply for our program #uniGoettingen covering a broad range of topics
uni-goettingen.de/de/657628.html
Marvel Universe looks almost like a real social network

We investigate the structure of the Marvel Universe collaboration network, where two Marvel characters are considered linked if they jointly appear in the same Marvel comic book. We show that this network is clearly not a random network, and that it has most, but not all, characteristics of "real-life" collaboration networks, such as movie actors or scientific collaboration networks. The study of this artificial universe that tries to look like a real one, helps to understand that there are underlying principles that make real-life networks have definite characteristics.

https://ar5iv.labs.arxiv.org/html/cond-mat/0202174
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Applications for summer course 'Analytical Connectionism' (28 Aug-8 Sep) are now open!
https://www.ucl.ac.uk/gatsby/analytical-connectionism-2023

The course will introduce analytical methods for neural-network analysis & connectionist theories of higher-level cognition & psychology.
Biological Physics Comes of Age
Once an awkward confrontation between disciplines, biological physics is having its moment β€” and showing that life is not just a mess.

By William Bialek

https://aps.org/publications/apsnews/202304/biological.cfm
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#ComplexityPodcast with SFI External Prof Mason Porter about #NetworkScience tools for community detection and how #Topology reveals a hidden order in the flood of #Data:

complexity.simplecast.com/episodes/105
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#netsci2023 is proud to announce a limited number of travel grants for researchers from low and middle-income countries to attend the conference in person.

Head to our website for more details:
https://netsci2023.wixsite.com/netsci2023/calls
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Every Author as First Author
Erik D. Demaine, Martin L. Demaine

We propose a new standard for writing author names on papers and in bibliographies, which places every author as a first author -- superimposed. This approach enables authors to write papers as true equals, without any advantage given to whoever's name happens to come first alphabetically (for example). We develop the technology for implementing this standard in LaTeX, BibTeX, and HTML; show several examples; and discuss further advantages.

https://arxiv.org/abs/2304.01393
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The University of Glasgow is recruiting a social network #PhD student to study peer-led interventions, using advanced simulation techniques (i.e., Siena simulations or agent-based modelling).
Applications deadline 13/4/23
Full info
https://t.co/yrVRVnKJJu
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The Department of Statistics (Stockholm University) is hiring 1-2 #PhD students. Deadline 25/4/23.
Students interested in statistical inference and modelling of network data are very welcomed!

https://www.su.se/english/about-the-university/work-at-su/available-jobs/phd-student-positions-1.507588?rmpage=job&rmjob=20423&rmlang=UK
Notions and methods rooted in or with strong flavour of statistical physics that have been applied to study the
structural, dynamical or control properties of complex networks

Controlling complex networks with complex nodes
https://www.nature.com/articles/s42254-023-00566-3
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Notions and methods from control theory that have been applied to analyse and control complex networks

Controlling complex networks with complex nodes
https://www.nature.com/articles/s42254-023-00566-3
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We are looking for an enthusiastic and motivated candidate from the fields of computational biology, mathematics, computational physics, engineering, and similar for a #PhD position in a DFG-funded research project "Association between abundance structure and biodiversity patterns as a signature of deterministic processes".

https://www.linkedin.com/jobs/view/3517580042/?refId=PEsKJ8Ia%2FXOuXnOk21FlpA%3D%3D&trackingId=PEsKJ8Ia%2FXOuXnOk21FlpA%3D%3D
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fully-funded #PhD student (up to 5 years) at the intersection of comp neuro 🧠 and ML πŸ€–

πŸ‘‰ sprekelerlab.org/jobs/
Unifying Pairwise Interactions in Complex Dynamics
Oliver M. Cliff, Joseph T. Lizier, Naotsugu Tsuchiya, Ben D. Fulcher
arxiv.org/abs/2201.11941


Scientists have developed hundreds of techniques to measure the interactions between pairs of processes in complex systems. But these computational methods -- from correlation coefficients to causal inference -- rely on distinct quantitative theories that remain largely disconnected. Here we introduce a library of 249 statistics for pairwise interactions and assess their behavior on 1053 multivariate time series from a wide range of real-world and model-generated systems. Our analysis highlights new commonalities between different mathematical formulations, providing a unified picture of a rich, interdisciplinary literature. We then show that leveraging many methods from across science can uncover those most suitable for addressing a given problem, yielding high accuracy and interpretable understanding. Our framework is provided in extendable open software, enabling comprehensive data-driven analysis by integrating decades of methodological advances.
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