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Ambitions for theory in the physics of life
William Bialek
SciPost Phys. Lect. Notes 84 (2024)
Dear all,
Bernstein Center for Computational Neuroscience Berlin is happy to announce that they have two DAAD-funded scholarships for doctoral students available ℹ️

They will select two excellent doctoral student candidates to receive scholarships from the DAAD as part of the Graduate School Scholarship Program (GSSP).
    The scholarships begin in October 2026 à 1,300€/ month, for up to a maximum of 4 years,
    In addition to the scholarship, health insurance, accident insurance, and liability insurance will be covered by the DAAD,
    Scholarship recipients can also receive assistance for their rent payments,
    Scholarship recipients with families may receive additional funding,
    Scholarship recipients will have access to a country-specific travel budget from the DAAD,
    Scholarship recipients will have access to additional Study and Research grants,
    Can have German courses financed by the DAAD.

To be eligible for the GSSP scholarships, the student must:
    Have an excellent academic profile and must have completed their master's (or equivalent) by the start of the funding period (October 2026),
    Can not have completed their master's (or equivalent) more than 6 years ago,
    At the time of application (March 2026), can not have been a resident in Germany for more than 15 months,
    Can not already have a PhD,
    Can not perform more than 25% of their doctoral work outside of Germany, and external work can not take place at the start of the doctoral project.

To be awarded the GSSP scholarship, the student must:
Apply to the BCCN PhD program -->Application deadline March 15th 2026!
A member of the BCCN Berlin must agree to supervise and accept the student to their group for the duration of their PhD.
A project proposal outlining the general goals of the doctoral project must have been agreed upon by the student and the BCCN Berlin supervisor by the application deadline. 

For more information on how to apply to the International Doctoral Program Computational Neuroscience of the BCCN Berlin, please see our website:
https://www.bccn-berlin.de/doctoral-program-application.html

Finally, we organize an Information session about our graduate programs which will take place in January 2026:
https://www.bccn-berlin.de/events-list/information-day-2026-international-graduate-programs-computational-neuroscience.html

Please share this information with anyone who may be interested.
The Physics of News, Rumors, and Opinions

The boundaries between physical and social networks have narrowed with the advent of the Internet and its pervasive platforms. This has given rise to a complex adaptive information ecosystem where individuals and machines compete for attention, leading to emergent collective phenomena. The flow of information in this ecosystem is often non-trivial and involves complex user strategies from the forging or strategic amplification of manipulative content to large-scale coordinated behavior that trigger misinformation cascades, echo-chamber reinforcement, and opinion polarization. We argue that statistical physics provides a suitable and necessary framework for analyzing the unfolding of these complex dynamics on socio-technological systems. This review systematically covers the foundational and applied aspects of this framework. The #review is structured to first establish the theoretical foundation for analyzing these complex systems, examining both structural models of complex networks and physical models of social dynamics (e.g., epidemic and spin models). We then ground these concepts by describing the modern media ecosystem where these dynamics currently unfold, including a comparative analysis of platforms and the challenge of information disorders. The central sections proceed to apply this framework to two central phenomena: first, by analyzing the collective dynamics of information spreading, with a dedicated focus on the models, the main empirical insights, and the unique traits characterizing misinformation; and second, by reviewing current models of opinion dynamics, spanning discrete, continuous, and coevolutionary approaches. In summary, we review both empirical findings based on massive data analytics and theoretical advances, highlighting the valuable insights obtained from physics-based efforts to investigate these phenomena of high societal impact.

https://arxiv.org/abs/2510.15053
#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.
2025/10/28 09:33:50
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