Looking for a #PhD-Position in #QuantumPhysics with a Focus on #TensorNetworks? 👩‍🎓👨‍🎓 Then join our "Quantum Information and Quantum Many-Body Physics"-Research Group, led by Norbert Schuch! ✨ Info on how to apply is available at https://t.co/CIT9g7iITB

Do you want to enter the exciting world of #ComplexSystems? 🔍
📣Pre-registration open!

IFISC offers mobility fellowships to study the IFISC Master in Physics of #ComplexSystems, one of them is sponsored by @F_Sicomoro

ℹ https://t.co/d629pXL8oS

New paper from Duncan J Watts: Theories of organizations are sympathetic to long-standing ideas from network science that organizational networks should be regarded as multiscale and capable of displaying emergent properties. However, the historical difficulty of collecting individual- level network data for many (N ≫ 1) organizations, each of which comprises many (n ≫ 1) individuals, has hobbled efforts to develop specific, theoretically motivated hypotheses connecting micro- (i.e., individual-level) network structure with macro-organizational properties. In this paper we seek to stimulate such efforts with an exploratory analysis of a unique data set of aggregated, anonymized email data from an enterprise email system that includes 1.8 billion messages sent by 1.4 million users from 65 publicly traded U.S. firms spanning a wide range of sizes and 7 industrial sectors. We uncover wide hetero- geneity among firms with respect to all measured network characteristics, and we find robust network and organizational variation as a result of size. Interestingly, we find no clear associations between organizational network structure and firm age, industry, or performance; however, we do find that centralization increases with geographical dispersion—a result that is not explained by network size. Although preliminary, these results raise new questions for organizational theory as well as new issues for collecting, processing, and interpreting digital network data.

Coming up soon: a mooc to learn machine learning in Python with #scikit_learn
https://t.co/mkf8g2x44x

8 weeks, 4.5Hrs/wk, from zero to hero in machine learning: from knowing only basic Python to understanding ML

درس فیزیک دستگاه‌های پیچیده
دکتر سامان مقیمی - دانشکده فیزیک، دانشگاه صنعتی شریف

https://www.aparat.com/playlist/838442

👍 The 2nd edition of 'The Hitchhiker's Guide to #CondensedMatter and #StatisticalPhysics: Topological Phenomena in Condensed Matter', an ICTP Virtual School, will be held (virtually) on 6th, 13th, 20th May and 3rd June 2021.

Register here by 30 April: https://t.co/yZmES8AvTw

📺 Opinion Dynamics on Networks: http://video.albanova.se/ALBANOVA20210422/video.mp4

I survey three different types of opinion models (with examples of each from my work): threshold models, voter models, and bounded-confidence models.

📺 Computational Epidemiology at the time of COVID-19 by @alexvespi https://t.co/UwPUhsCuzL https://t.co/1EslXAl3Xy

💰 We're still accepting applications for our #PhD project in Characterizing Temporal Social Networks using Dynamic Embeddings.

https://t.co/NMHPFB0xCI

The project is part of a larger study to develop computational tools for the analyses of large dynamic complex networks.

18 tips for giving a horrible presentation - Do they sound familiar?

https://retractionwatch.com/2016/11/30/18-tips-giving-horrible-presentation/

🔴انجمن علمی مهندسی کامپیوتر دانشگاه کردستان، برگزار می‌کند:

🔰مباحث ویژه در نظریه اطلاعات و شبکه‌های پیچیده

🔷سخنران: آرشام غواصیه، دانشجوی دکتری فیزیک ترنتوی ایتالیا و پژوهشگر سیستم‌ها و شبکه‌های پیچیده

🗓یکشبنه 5 اردیبهشت 1400
⏰ساعت 13

🔶شرکت در وبینار برای عموم آزاد و رایگان است

🔷ورود بدون نیاز به نام کاربری و رمز عبور است و تنها کافی است با گزینه مهمان وارد شوید

🔗آدرس وبینار:
meet.uok.ac.ir/ch/eng.hall5

🆔@uok_comp

May 3, 2021 Submission deadline
May 10, 2021 Notification
May 17, 2021 Camera Ready Copy

Fund waivers are available for students from developing countries who are not able to pay for the conference.
Contact Fariba Karimi: karimi@csh.ac.at

https://websci21.webscience.org/call-for-phd-symposium

💉 #COVID19 good news 👏

A study analysing 373,402 participants finds COVID-19 infections fell significantly after a single dose of the #OxfordVaccine or Pfizer jab.

More info ⬇️
https://www.ox.ac.uk/news/2021-04-23-significant-reductions-covid-19-infections-found-after-single-dose-oxford

💰Doctoral student in Computational Neuroscience
#phd in School of Electrical Engineering and Computer Science at KTH

https://facultyvacancies.com/doctoral-position-in-computational-neuroscience,i19433.html

Neuromodulators are crucial for the brain function and while the effect of neuromodulation is relatively well studied, little is known about how neuromodulators affect the network activity dynamics. In this project we want to quantify the effects of neuromodulators on neuron/synapse properties and network structure and dynamics.

The doctoral student will be part of Dr. Kumar's research group. The research group uses computational and analytical methods to understand the dynamics and information processing in biological neuronal networks. The research in the Kumar lab is aimed at understading:

The role of oscillations and correlations in communication between different brain areas [e.g. see Hahn et al. Nature Rev. Neurosci. 2019]
Control of brain activity dynamics [e.g. see Vlachos et al. PloS Comp Bio 2016]
Interaction between neuron properties and network activity dynamics [Sahasranamam et al. Sci. Reports 2015, Spreizer et al. PloS Comp Bio 2010, Hahn et al. 2020]
Neural coding [e.g. Tauffer and Kumar 2020].

The research group is also developing mathematical models of brain diseases to understand the mechanisms underlying the emergence of disease related aberrant activity dynamics in brain diseases. More info.: https://www.kth.se/profile/arvindku/

Supervision: The doctoral student will be supervised by: Dr. Arvind Kumar

💰#PhD Position in Neuro-Bioinformatics for Central Nervous System Repair
Catholic University of Leuven


https://facultyvacancies.com/phd-position-in-neuro-bioinformatics-for-central-nervous-system-repair,i19002.html

💰#PhD position (m/f/d; E13 TV-L, 80%) in Compositional Data Synthesis
Bosch Industry-on-Campus Lab, University of Tübingen and Bosch Center for AI (BCAI)

The aim of this project is to learn how to synthesize new, previously unseen visual scenes through object compositionality. A bias to account for the compositional way in which humans structure a visual scene in terms of objects has frequently been overlooked. In this project, you will investigate object compositionality as an inductive bias for deep generative models, such as generative adversarial networks (GANs). Specifically, you will focus on how to generate novel unseen compositions of objects present in the training set.

You will be jointly supervised by Prof. Dr. Zeynep Akata from the University of Tübingen side and Dr. Anna Khoreva from the Bosch side.

The position is available immediately (but start date is negotiable), the contract is initially for three years, and remunerated according to the German salary scale 13 TVL.

https://facultyvacancies.com/phd-position-in-compositional-data-synthesis,i19854.html

How Maxwell’s Demon Continues to Startle Scientists

The thorny thought experiment has been turned into a real experiment — one that physicists use to probe the physics of information.

https://www.quantamagazine.org/how-maxwells-demon-continues-to-startle-scientists-20210422/

نظریه اطلاعات و شبکه های پیچیده

افتخار داشتم به دعوت دکتر عبدالله پوری عزیز در مورد جنبه هایی از کارم با اساتید عزیز و دانشجویان دانشگاه کردستان و سایر عزیزانی که شرکت کردند صحبت کنم. تخصص بیشتر حاضرین کامپیوتر بود، برای همین جنبه های فیزیکی کار رُ گذرا گفتم و رسیدم به کاربرد ها.
یک بار دیگه ممنونم از دکتر عبدالله پوری و سایر اساتید و عزیزان خودم که به من گوش کردند. ضمنا خستگی صدای من به خاطر صبحونه نخوردنه. :)

مخلص

@physics_daily

5/اردیبهشت/1400

Chaotic dynamics along the Lorenz attractor

Video on reduction to a 1D map, the Lorenz map
https://t.co/FPUJ0sbSyM

#ChaosTheory #Fractals #chaos #mathart #DynamicalSystems #NonlinearDynamics #LorenzAttractor #math #maths #manifold