Doctoral Researcher in analyzing nature visit typologies using big data

#phd https://jobs.helsinki.fi/job/Helsinki-Doctoral-Researcher-in-analyzing-nature-visit-typologies-using-big-data/784269202/?

We are looking for a #postdoc researcher to work on an innovative approach for user-centric partitioning of complex networks (telecom networks, energy networks, social networks, etc.).

The required skills are in optimization (mathematical programming, meta/mat-heuristics), algorithms, and analysis of complex networks.

Cécile Bothorel

#phd Networks and graphs - both static and dynamic

https://www.kuleuven.be/personeel/jobsite/jobs/60288125

Applications for the “ENS Junior Research Laplace chair” are open. data-ens.github.io/jobs/
We are looking for outstanding candidates in data sciences. The selected candidate will work as an independent #postdoc at the center for data sciences of Ecole Normale Supérieure (Paris)

#Postdoc Positions at the Center for Network Dynamics, Northwestern University

https://cnd.northwestern.edu/openings/

#phd & #postdoc
uvm.edu/socks/#jobs

Critical phenomena in complex networks: from scale-free to random networks

Within the conventional statistical physics framework, we study critical phenomena in configuration network models with hidden variables controlling links between pairs of nodes. We obtain analytical expressions for the average node degree, the expected number of edges in the graph, and the Landau and Helmholtz free energies. We demonstrate that the network’s temperature controls the average node degree in the whole network. We also show that phase transition in an asymptotically sparse network leads to fundamental structural changes in the network topology. Below the critical temperature, the graph is completely disconnected; above the critical temperature, the graph becomes connected, and a giant component appears. Increasing temperature changes the degree distribution from power-degree for lower temperatures to a Poisson-like distribution for high temperatures. Our findings suggest that temperature might be an inalienable property of real networks.

https://link.springer.com/article/10.1140/epjb/s10051-023-00612-0

LAKE COMO SCHOOL OF ADVANCED STUDIES

Spring School "Computational Social Science: Advances, Challenges and Opportunities (1st edition)"

Villa del Grumello, Como, Italy, May 13-17 2024

https://css.lakecomoschool.org/

Does the brain behave like a (complex) network? I. Dynamics
https://www.sciencedirect.com/science/article/pii/S1571064523002105

#job Data Scientist - Computational Social Science Lab

https://wd1.myworkdaysite.com/en-US/recruiting/upenn/careers-at-penn/job/3401-Walnut-Street/Data-Scientist---Computational-Social-Science-Lab_JR00084578

Link Me Baby One More Time: Social Music Discovery on Spotify

https://arxiv.org/abs/2401.08818

#PhD at ITU at the intersection of AI, Network Science and Computational Social Science

https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181658&DepartmentId=3439&MediaId=5

Fast degree-preserving rewiring of complex networks

https://arxiv.org/abs/2401.12047

Mark Newman | Leaders and Best: Networks and Ranking in Sports, Markets, and Society

One of the oldest of network problems is the ranking of individuals, teams, or commodities on the basis of pairwise comparisons between them. For example, if you know which football teams beat which others in a particular year, can you say which team is the best overall? This is a harder problem than it sounds because not all pairs of teams play games in a given season, and also because the outcomes of the games can be ambiguous or contradictory. This talk will introduce the techniques used to solve such ranking problems, with examples from games and sports, consumer research and marketing, and social hierarchies in both animal and human communities, then ask how those techniques can be extended to answer a range of new questions about competition and ranking, including the development of new computer algorithms for ranking, questions about the varying patterns of competition in different sports, and what happens when individuals or teams compete in multiple different ways.

https://www.mivideo.it.umich.edu/playlist/dedicated/293581272/1_gz6diy1y/1_ke40xxtk

"Ambitions for theory in the physics of life" (by William Bialek): https://arxiv.org/abs/2401.15538

[note: Lectures at the 2023 Les Houches Summer School, Theoretical Biophysics]

Theoretical physicists have been fascinated by the phenomena of life for more than a century. As we engage with more realistic descriptions of living systems, however, things get complicated. After reviewing different reactions to this complexity, I explore the optimization of information flow as a potentially general theoretical principle. The primary example is a genetic network guiding development of the fly embryo, but each idea also is illustrated by examples from neural systems. In each case, optimization makes detailed, largely parameter-free predictions that connect quantitatively with experiment

Up to 6 fully-funded #PhD positions in Data Science for Oct 2024, Trieste (Italy): 4 years, no restriction on nationality - applications from candidates from under-represented groups especially encouraged!

http://datascience.sissa.it/apply

Multiple #Postdoc positions in Budapest
https://centerforcollectivelearning.org/jobs

The Computational Inequalities Research Group, led by Orsolya Vásárhelyi is looking for two Postdoctoral Research Fellows for full-time positions (40 hours/week) at the Center for Collective Learning (CCL) at Corvinus University at the Corvinus University of Budapest.