How to Make Your Research and Code Reproducible and Reusable?

https://youtu.be/SyQl8kJvSxs

00:00 Introduction
01:42 Beginning of the presentation by Mika Jalava
03:25 What is research reproducibility?
06:01 Reproducibility crisis
07:43 Why is reproducibility so important? Who should care?
10:15 What deters reproducibility?
18:33 Importance of the whole computational environment
20:17 What is "computational environment"?
26:02 Random effects
29:06 Human-side of the reproducibility crisis
33:07 Requirements for reproduction
35:58 What can we do to improve reproducibility?
39:23 Practical take-home

How are people able to map knowledge from one domain to another? I'll report a series of studies showing that people's cross-domain mappings were best predicted by similarity along abstract dimensions such as valence, complexity, and genderedness - a finding that could be reliably simulated by language models. In an ongoing study, we further asked what allows people to process cross-domain mappings so easily by drawing insights from a network perspective.

https://www.youtube.com/watch?v=DkiCE8rBi9k

Hopfield network: How are memories stored in neural networks? [Nobel Prize in Physics 2024]

https://youtu.be/piF6D6CQxUw

Open #PhD and #postdoc positions in neuroscience

https://www.keshavarzilab.com/

5 lectures on Theory of Large Deviations and Applications by Pierpaolo Vivo

https://t.co/1grOMbOv3X
https://t.co/38SeBWgYBr
https://t.co/nxn1XgFDCX
https://t.co/YED2gx2EQr
https://t.co/4ZlIIvE96p

a #postdoc to work on a project modeling the knowledge space and the role of scientific funding in technological advancement.

https://osome.iu.edu/research/blog/postdoctoral-fellow-opening

Reality-inspired voter models: A mini-review
Sidney Redner

This mini-review presents extensions of the voter model that incorporate various plausible features of real decision-making processes by individuals. Although these generalizations are not calibrated by empirical data, the resulting dynamics are suggestive of realistic collective social behaviors.

https://www.sciencedirect.com/science/article/pii/S1631070519300325

Opinion dynamics in social networks: From models to data
Antonio F. Peralta, János Kertész, Gerardo Iñiguez

Opinions are an integral part of how we perceive the world and each other. They shape collective action, playing a role in democratic processes, the evolution of norms, and cultural change. For decades, researchers in the social and natural sciences have tried to describe how shifting individual perspectives and social exchange lead to archetypal states of public opinion like consensus and polarization. Here we review some of the many contributions to the field, focusing both on idealized models of opinion dynamics, and attempts at validating them with observational data and controlled sociological experiments. By further closing the gap between models and data, these efforts may help us understand how to face current challenges that require the agreement of large groups of people in complex scenarios, such as economic inequality, climate change, and the ongoing fracture of the sociopolitical landscape.

https://arxiv.org/abs/2201.01322

From classical to modern opinion dynamics
Hossein Noorazar, Kevin R. Vixie, Arghavan Talebanpour, Yunfeng Hu

In this age of Facebook, Instagram and Twitter, there is rapidly growing interest in understanding network-enabled opinion dynamics in large groups of autonomous agents. The phenomena of opinion polarization, the spread of propaganda and fake news, and the manipulation of sentiment are of interest to large numbers of organizations and people, some of whom are resource rich. Whether it is the more nefarious players such as foreign governments that are attempting to sway elections or large corporations that are trying to bend sentiment -- often quite surreptitiously, or it is more open and above board, like researchers that want to spread the news of some finding or some business interest that wants to make a large group of people aware of genuinely helpful innovations that they are marketing, what is at stake is often significant. In this paper we review many of the classical, and some of the new, social interaction models aimed at understanding opinion dynamics. While the first papers studying opinion dynamics appeared over 60 years ago, there is still a great deal of room for innovation and exploration. We believe that the political climate and the extraordinary (even unprecedented) events in the sphere of politics in the last few years will inspire new interest and new ideas. It is our aim to help those interested researchers understand what has already been explored in a significant portion of the field of opinion dynamics. We believe that in doing this, it will become clear that there is still much to be done.

https://arxiv.org/abs/1909.12089

#PhD students at Berkeley:
if you are interested in ML applied to health, inequality, or social science, and mention Emma Pierson in your app.

More details on work/how to apply: https://cs.cornell.edu/~emmapierson/

Steven Strogatz: Global Synchronization: New Theorems, New Puzzles

https://youtu.be/0l-UwTLiIX4

#Postdoc Position: Multimodal Signalling in Face-to-Face Communication at the Donders Centre for Cognition

https://www.ru.nl/en/working-at/job-opportunities/postdoc-position-multimodal-signalling-in-face-to-face-communication-at-the-donders-centre-for-cognition

Fast unfolding of communities in large networks: 15 years later

The Louvain method was proposed 15 years ago as a heuristic method for the fast detection of communities in large networks. During this period, it has emerged as one of the most popular methods for community detection: the task of partitioning vertices of a network into dense groups, usually called communities or clusters. Here, after a short introduction to the method, we give an overview of the different generalizations, modifications and improvements that have been proposed in the literature, and also survey the quality functions, beyond modularity, for which it has been implemented. Finally, we conclude with a discussion on the limitations of the method and perspectives for future research.

https://iopscience.iop.org/article/10.1088/1742-5468/ad6139

#PhD position in Digital Chemistry

project on combining traditional expert features with deep learning for reaction prediction.
https://www.jobs.ethz.ch/job/view/JOPG_ethz_4etBDEk8lO4Z8W71Q8

Where postdoctoral journeys lead?
https://arxiv.org/abs/2411.03938

The prestige of a PhD-granting institution is well known for influencing faculty hiring and career progression in American academia. But what about the postdoc stage—what impact does it have on shaping academic careers globally?

Based on the data*, high-impact publications and mobility with a little twist over the research topic during the postdoc are key to enhancing your academic career. Surprisingly, the prestige of the institution you move to is less influential than expected. So, regardless of your success in PhD, your odds improve by making moderate shifts in research focus and location with significant shifts in publication quality.

*: The authors used a comprehensive dataset by combining publication records from the Microsoft Academic Graph (MAG) with career data from a major online professional network. Spanning 25 years and encompassing 45,572 careers from various disciplines, the dataset specifically examines the influence of postdoctoral experiences on early academic success—considering factors like relocation, topic change, and early high-impact publications.

Science Writing Fellow, Quanta Magazine

Quanta Magazine is looking for an early-career science journalist for its spring 2025 writing fellowship. This six-month program will give the successful applicant extensive experience writing news and features about one or more areas that Quanta covers: physics, mathematics, biology and computer science.

https://simonsfoundation.wd1.myworkdayjobs.com/en-US/simonsfoundationcareers/job/Science-Writing-Fellow_R0001723

Two fully funded #PhD students and #postdoc at Trinity College Dublin

https://tahayasseri.com/join/

On the foundations of statistical mechanics
https://arxiv.org/abs/2411.08709

The Department of Statistics and Data Science at Carnegie Mellon University invites applicants for a two-year #postdoc fellowship in simulation-based inference. The fellow will work with Prof. Cosma Shalizi of the department on developing theory, algorithms and applications of random feature methods in simulation-based inference, with a particular emphasis on social-scientific problems connected to the work of CMU's Institute for Complex Social Dynamics. Apart from by the supervisor, the fellow will also be mentored by other faculty in the department and the ICSD, depending on their interests and secondary projects, and will get individualized training in both technical and non-technical professional skills.

Successful applicants will have completed a Ph.D. in Statistics, or a related quantitative discipline, by September 2025, and ideally have a strong background in non-convex and stochastic optimization and/or Monte Carlo methods, and good programming and communication skills. Prior familiarity with simulation-based inference, social network models and agent-based modeling will be helpful, but not necessary.

https://apply.interfolio.com/159056

The Department of Statistics and Data Science and the Institute for Complex Social Dynamics at Carnegie Mellon University invite applicants for a two-year #postdoc fellowship in social network dynamics. The fellow will work with Prof. Nynke Niezink of the department on developing theory, statistical methodology and applications of models for longitudinal network data, with a particular emphasis on social-scientific problems connected to the work of the Institute. Apart from by the supervisor, the fellow will also be mentored by other faculty in the department and the ICSD, depending on their interests and secondary projects, and will get individualized training in both technical and non-technical professional skills.

https://apply.interfolio.com/159058