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علوم اجتماعی محاسباتی چیه؟
آینده‌ش چه جوریه؟


علوم اجتماعی محاسباتی (Computational Social Science) یک شاخه جدید و میان‌رشته‌ای است که علاوه بر روش‌های سنتی مانند نظرسنجی‌ها، از ابزارهای محاسباتی و داده‌هایی مثل فعالیت‌های آنلاین، شبکه‌های اجتماعی و اطلاعات دیجیتال برای مطالعه و تحلیل رفتارها و روابط اجتماعی استفاده می‌کند.

این علم به ما کمک می‌کند تا الگوهای پیچیده در جوامع انسانی را بهتر بفهمیم، رفتارهای گروهی را پیش‌بینی کنیم، و تأثیر سیاست‌ها یا رویدادهای مختلف را بر جامعه ارزیابی کنیم. به طور خلاصه، علوم اجتماعی محاسباتی ترکیبی از داده‌ها، فناوری و تحلیل‌های اجتماعی است تا تصویری دقیق‌تر از جهان اجتماعی ارائه دهد.

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#سیتپـــــور به خاطر روایتگری در علم
#Postdoc in social network emergence and methodology at SODAS! 👀

This postdoc is part of a larger project called ‘New computational approaches for understanding the emergence of social network structures’, funded by the Novo Nordisk Foundation. The postdoc will likely work on exploring a new idea for how information about underlying processes can be extracted from network data, in collaboration with the project team.

The deadline for applications is: 23:59 CETS on October 6, 2024

Apply and read more here: https://lnkd.in/e9pmwJYP
#PhD fellowship in the emergence of social network structures at SODAS

Social networks (the patterns of social interactions between individuals) show high structural diversity across humans and non-human animal species, and these structures affect important processes such as the spread of disease and information. This PhD is part of a larger project called ‘New computational approaches for understanding the emergence of social network structures’, funded by the Novo Nordisk Foundation.

The deadline for applications is: 23:59 CETS on October 6, 2024

Apply and read more here: https://lnkd.in/e3cgUgpY
#Postdoc fellow in Philosophy of AI & Socially-Aware Artificial Intelligence

Department of Historical, Philosophical and Religious Studies

https://www.umu.se/en/work-with-us/open-positions/postdoctoral-fellow-in-philosophy-of-ai--socially-aware-artificial-intelligence_746500/
Winter Workshop on Complex Systems between January 26th and 31st in the mountains of Lombardy, Italy.

Please complete your application by October 13th, 2024! Check out the website (https://wwcs2025.github.io/) or our X-page (https://x.com/winter_complex) for more updates. 
#PhD student positions in Active Matter and Statistical Physics. The research area will build on ongoing projects in the group, such as non-reciprocal active matter. Information on how to apply at the link below:

https://www.ds.mpg.de/4068011/job_full_offer_23470793
#postdocs in AI, ML, Cogsci, or related areas: apply to work with me and others on AI models of visual and multimodal reasoning. Two years of funding with possible extension to a third year.

Application deadline November 22.

https://santafe.edu/about/jobs/postdoc-ai-modeling
A 2019 study, by looking at citation networks, found that papers with more authors tend to receive more citations — large teams are good at developing a field. However, they found that the smallest teams — between one and three authors — were significantly more likely to publish disruptive results that could change the course of a field. So, in terms of sheer creativity, smaller groups seem to have an advantage.

https://www.nature.com/articles/s41586-019-0941-9
The 2024 #NobelPrize laureates in physics used tools from physics to construct methods that helped lay the foundation for today’s powerful machine learning.

The Hopfield network can store patterns and has a method for recreating them. When the network is given an incomplete or slightly distorted pattern, the method can find the stored pattern that is most similar.

Read more about the research that led to this year’s physics prize: https://bit.ly/3Bi9H8u
How to Make Your Research Reproducible

Science is about standing on the shoulders of giants – making new discoveries and building new applications by reusing foundations laid by others. But however collaborative a process science is, we don’t always make it easy. Have you ever tried but failed to reproduce someone else's reported research results? How about your own results? According to scientific research, this is not uncommon in academia, which has led to the phenomenon being dubbed as "the reproducibility crisis". And reproducibility is just the first step of reusability.

In this webinar, we will discuss the challenges in reproducibility and reusability of scientific data, methods, and computer code. What do the terms really mean and how can we take steps to improve our work to take them into account.

https://www.aalto.fi/en/events/how-to-make-your-research-reproducible-oct-24-2024
#postdoc researcher to join the Inverse Complexity Lab at IT:U, Linz, Austria.

https://skewed.de/lab/call.html

Deadline is 30 Nov 2024.
2025/06/19 11:32:53
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