Finite Markov chains and Monte-Carlo Methods: An Undergraduate Introduction

https://arxiv.org/abs/2510.14165

Are these the happiest PhD students in the world?
https://www.nature.com/articles/d41586-025-03346-4

what matters most [is] human connections, meaningful work and mentorship.

David Chalmers, Can There Be a Mathematical Theory of Consciousness? | Natural Philosophy Symposium

https://youtu.be/ZsvePdaYw7M

Program: Is it time to bring back natural philosophy?

https://www.abc.net.au/listen/programs/philosopherszone/is-it-time-to-bring-back-natural-philosophy-/105499206

Daniel Dennett, How, When, and Why Can We Trust Our Brains? | Natural Philosophy Forum Lecture, 2023
https://youtu.be/32u12zjgJww

Sandra Mitchell, Biological Complexity and Scientific Practice | Natural Philosophy Symposium 2025

https://youtu.be/OamFDuT45oY?list=PLWDzKuETVzrpkaD32TBFn8sarleSfLJ3A

Transmission Versus Truth: What Will It Take to Make an Al as Smart as a 4-Year-Old?

https://youtu.be/PNE5pfQBlxM

#PhD opportunity to predict how natural populations will respond to perturbations:
https://www.findaphd.com/phds/project/social-manipulations-for-predicting-wild-animal-societies-responses-to-perturbations/?p187979

The project will combine large-scale social data from model animal systems with network analyses and social manipulations to understand the causal effects of external forces on real-world societies.
Application Deadline 7 Jan 2026, fully funded through YES-DTN scheme at University of Leeds.

#phd Developing methods for accurate reconstruction of viral histories to guide pandemic preparedness and targeted interventions
https://www.ndm.ox.ac.uk/study/dphil-themes?project=developing-methods-for-accurate-reconstruction-of-viral-histories-to-guide-pandemic-preparedness-and-targeted-interventions

About Philip Warren Anderson

https://arxiv.org/abs/2510.20865

Shark Data Suggests Animals Scale Like Geometric Objects

https://www.quantamagazine.org/shark-data-suggests-animals-scale-like-geometric-objects-20251027/

Lake Como School: Complex Networks
Theory, Methods, and Applications - May 18-22, 2026

https://ntml.lakecomoschool.org/

Senior Scientist (= #PostDoc with option of permanency)!

https://jobs.uni-graz.at/en/jobs/7d1400f4-cbe6-ab69-dc82-68e77675d81c?category=Academic%20Staff%20(Non-Tenure-Track),Academic%20Staff%20(Development%20Position)

Towards an Understanding of Scientific Disagreement
https://vimeo.com/1131827105

🔺🔺🔺Postdoc Opportunity – Electrophysiology Lab (Shahid Beheshti University)

Dr. Reza Lashgari is looking for postdoctoral researchers to join his electrophysiology lab at Shahid Beheshti University.
Candidates with a strong background in neuroscience, signal recording, and signal processing are encouraged to apply.

Please share this with anyone who might be interested!

Simon DeDeo, Hard Proofs and Good Reasons | Natural Philosophy Symposium 2025
https://youtu.be/JJLBZ4C1OGw

Reticula: A temporal network and hypergraph analysis software package

Abstract: In the last decade, temporal networks and static and temporal hypergraphs have enabled modelling connectivity and spreading processes in a wide array of real-world complex systems such as economic transactions, information spreading, brain activity and disease spreading. Here, we present the Reticula C++ library and Python package: A comprehensive suite of tools for working with real-world and synthetic static and temporal networks and hypergraphs. This includes various methods of creating synthetic networks and randomised null models based on real-world data, calculating reachability and simulating compartmental models on networks. The library is designed principally on an extensible, cache-friendly representation of networks, with an aim of easing multi-thread use in the high-performance computing environment.

In terms of challenges, I will talk more generally about the good and bad parts of writing and distributing software by scientists for scientists. What kind of skills would be useful? How can a PhD candidate reconcile scientific software development with the classic expectation of publishing papers and getting citations?

Speaker: Arash Badie-Modiri

https://youtu.be/k_psA5l07zQ

#Postdoc position for Generative models for molecular dynamics

https://www.chalmers.se/en/about-chalmers/work-with-us/vacancies/?rmpage=job&rmjob=14027&rmlang=UK

First, I’ll re-introduce Metropolis-Hastings, the algorithm behind Gibbs Sampling and similar Markov chain algorithms. I assume most readers have at least heard of it. Instead of mathematical rigor, I’ll animate the approach so that the reader can appreciate both why it works and why it cannot scale with our inferential ambitions. Second, I’ll introduce Hamiltonian Monte Carlo, a very different approach to constructing Markov chains. Again, the goal is not to be mathematically precise, but to animate the algorithm and show why it works and why it still has limits.

https://elevanth.org/blog/2017/11/28/build-a-better-markov-chain/

Contact structure and population immunity shape the selective advantage of emerging variants.

Epidemics are shaped by the interplay between host and pathogen population characteristics, which are themselves intertwined. In particular, host behavior and immunity profile shape pathogen population structure by affecting both the likelihood of new variant emergence and its subsequent dynamics. Theoretical studies provided a fragmented description of this complex dynamical dependency, and the empirical evidence is limited. The SARS-CoV-2 pandemic presents an unprecedented opportunity to study the emergence of new variants. The relative growth of emerging variants over the resident ones, i.e., the selection coefficient, showed spatiotemporal variations that could be associated with population immunity and the mean and dispersion of contacts, which varied greatly according to epidemic intensity and human response. We first investigated the impact of these three features on the selection coefficient using a stochastic network-based model of new variant emergence, which incorporates tunable connectivity and heterogeneity. Results systematically chart the parameter space, uncover the boundaries of previously known associations, and quantify their strength. The mean number of contacts was positively associated with the selection coefficient, the effect being more robust for low immune-escape variants. The impact of immunity diminished as immunity increased. Importantly, greater contact dispersion slowed down the spread of variants lacking immune escape, but this effect quickly reversed once immune escape became non-zero. We then analysed the emergence of the SARS-CoV-2 Alpha variant in the United States at the state level, examining the association of the selection coefficient with the three population features under study, reconstructed from serological, vaccination, and contact survey data. Regression analyses revealed a strong effect of population characteristics. Comparing empirical trends with model predictions showed consistency and suggested that the selection coefficient was more affected by contact statistics than by immunity. These results shed light on how human population structure mediates variant dynamics and help interpret the heterogeneity observed in variant emergence.

https://www.medrxiv.org/content/10.1101/2025.11.07.25339691v1