Brain, Rain and Forest Fires -- What is critical about criticality: In praise of the correlation function
https://t.co/Fj5l8Fp3aX
https://t.co/Fj5l8Fp3aX
We are hiring! We are looking for a technician, a #PhD student, and a #postdoc to work on collective behaviour in nematodes starting this autumn. Join us!
https://t.co/RkY2SqzGZm, https://t.co/RupDQzIuLj, https://t.co/rbRt8xiulz
https://t.co/RkY2SqzGZm, https://t.co/RupDQzIuLj, https://t.co/rbRt8xiulz
#PhD Candidate in Molecular Neurobiology and Electrophysiology
My lab is hiring! An exciting opportunity for anyone interested in using state-of-the-art systems neuroscience and molecular approaches for studying neural and molecular mechanisms supporting memory maturation
https://t.co/bPepFVrEVP
My lab is hiring! An exciting opportunity for anyone interested in using state-of-the-art systems neuroscience and molecular approaches for studying neural and molecular mechanisms supporting memory maturation
https://t.co/bPepFVrEVP
solliciteren.ru.nl
De vacature bestaat niet (meer)
Vacature-overzicht Radboud Universiteit: https://www.ru.nl/vacatures
Graph Neural Networks as Neural Diffusion PDEs
Graph neural networks (GNNs) are intimately related to differential equations governing information diffusion on graphs. Thinking of GNNs as partial differential equations (PDEs) leads to a new broad class of GNNs that are able to address in a principled way some of the prominent issues of current Graph ML models such as depth, oversmoothing, bottlenecks, and graph rewiring.
https://michael-bronstein.medium.com/graph-neural-networks-as-neural-diffusion-pdes-8571b8c0c774
Graph neural networks (GNNs) are intimately related to differential equations governing information diffusion on graphs. Thinking of GNNs as partial differential equations (PDEs) leads to a new broad class of GNNs that are able to address in a principled way some of the prominent issues of current Graph ML models such as depth, oversmoothing, bottlenecks, and graph rewiring.
https://michael-bronstein.medium.com/graph-neural-networks-as-neural-diffusion-pdes-8571b8c0c774
Medium
Graph Neural Networks as Neural Diffusion PDEs
Graph neural networks are intimately related to partial differential equations governing information diffusion on graphs.
#PhD Positions in Physics, Mathematics, Engineering or Computer Sciences
BCAM Basque Center for Applied Mathematics - Spain
Deadline: 30th June 2021, 14:00 CET (UTC+1) .
Applications will be evaluated in a continuous manner, with a response period no longer than 4 weeks after the call deadline.
To apply click here.
BCAM Basque Center for Applied Mathematics - Spain
Deadline: 30th June 2021, 14:00 CET (UTC+1) .
Applications will be evaluated in a continuous manner, with a response period no longer than 4 weeks after the call deadline.
To apply click here.
Scholarships of $35,000 (AUD) are available for PhD students who achieved High Distinction (H1) in their undergraduate program and/or have completed a Masters by Research.
https://research.unsw.edu.au/people/dr-alireza-abbasi
Dr Alireza Abbasi is the Director of Postgraduate Studies at the School of Engineering and IT at UNSW Canberra. His research aims to enhance better functioning and performance of complex socio-technical systems, which primarily lies in the emerging field of Social Computing, leveraging the capacity to collect and analyse data to reveal patterns of individual and group behaviour.
https://research.unsw.edu.au/people/dr-alireza-abbasi
Dr Alireza Abbasi is the Director of Postgraduate Studies at the School of Engineering and IT at UNSW Canberra. His research aims to enhance better functioning and performance of complex socio-technical systems, which primarily lies in the emerging field of Social Computing, leveraging the capacity to collect and analyse data to reveal patterns of individual and group behaviour.
#postdoc on complex networks, social dynamics, biodiversity, etc.
You have roughly one week left to apply: https://t.co/8fS2G7gIc8
You have roughly one week left to apply: https://t.co/8fS2G7gIc8
Umantis
6 Postdoc Positions "Biodiversity of Anthropocene Oceans: Networks, Flows and Systems Approaches for Boundary Crossing Research"
Layout AWI HIPP extern, englisch
Two pᴏsᴛᴅᴏᴄs ɪɴ ᴄᴏᴍᴘᴜᴛᴀᴛɪᴏɴᴀʟ sᴏᴄɪᴀʟ sᴄɪᴇɴᴄᴇ
We are looking for ambitious candidates who want to launch their research careers in a highly supportive and interdisciplinary environment.
#postdoc https://t.co/tCNTjZuuGG
We are looking for ambitious candidates who want to launch their research careers in a highly supportive and interdisciplinary environment.
#postdoc https://t.co/tCNTjZuuGG
liu.se
Vacancies
We are one of Sweden's best employers. Check out our job openings and apply directly!
Join us for #Computation in #ComplexSystems, a free course starting 19 July!
With SFI Prof Cris Moore you'll learn the deep ideas of theoretical #ComputerScience and cultivate insights to serve you everywhere from #math to #hysics to #biology:
https://t.co/QGd48M6A7K
#MOOCs
With SFI Prof Cris Moore you'll learn the deep ideas of theoretical #ComputerScience and cultivate insights to serve you everywhere from #math to #hysics to #biology:
https://t.co/QGd48M6A7K
#MOOCs
Forwarded from Twitter (𝕏) Media Downloader دانلود از ایکس و توییتر
a Twitter thread from tiagopeixoto
https://telegra.ph/a-Twitter-thread-from-tiagopeixoto-06-25
https://telegra.ph/a-Twitter-thread-from-tiagopeixoto-06-25
Telegraph
a Twitter thread from @tiagopeixoto
1. A new version of graph-tool is out! @graphtool https://graph-tool.skewed.de It includes a 5x speedup of the SBM inference multilevel algorithm for principled community detection! Let it rip on your very large networks! See the HOWTO here: https://graph…
Scikit-learn is one of the most popular Python libraries for machine learning.
So if you're getting into ML, it's some good tech to know.
In this course, @fishnets88 breaks down complex concepts into bitesize pieces and makes it all more approachable.
https://t.co/LOlTK5yAe2
So if you're getting into ML, it's some good tech to know.
In this course, @fishnets88 breaks down complex concepts into bitesize pieces and makes it all more approachable.
https://t.co/LOlTK5yAe2
freeCodeCamp.org
Python scikit-learn Tutorial – Machine Learning Crash Course
Scikit-learn is one of the most popular machine leaning libraries for Python. It provides many unsupervised and supervised learning algorithms that make machine leaning simpler. We just published a scikit-learn course on the freeCodeCamp.org YouTube channel.…
Swarm Robotics: Past, Present, and Future [Point of View] | IEEE Journals & Magazine | IEEE Xplore
https://ieeexplore.ieee.org/abstract/document/9460560
https://ieeexplore.ieee.org/abstract/document/9460560
Forwarded from Pooyan Goodarzi
Bangalore School on Statistical Physics
This is a pedagogical school, aimed at bridging the gap between masters-level courses and topics in statistical physics at the frontline of current research. It is intended for Ph.D. students, post-doctoral fellows and interested faculty members at the college and university level. The following courses will be offered.
- Nonequilibrium response theory by Urna Basu (RRI, Bengaluru, India)
- Topology in statistical physics by Subhro Bhattacharjee (ICTS, Bengaluru, India)
- Statistical mechanics of developed turbulence by Nigel Goldenfeld (University of Illinois, Urbana-Champaign, US)
- Statistical physics of rare events and large deviations by Yariv Kafri (Technion -
Israel Institute of Technology, Haifa, Israel)
https://www.icts.res.in/program/bssp2020/talks
https://www.youtube.com/playlist?list=PL04QVxpjcnjjTv4rkFGzLa1PgRceIdtYO
This is a pedagogical school, aimed at bridging the gap between masters-level courses and topics in statistical physics at the frontline of current research. It is intended for Ph.D. students, post-doctoral fellows and interested faculty members at the college and university level. The following courses will be offered.
- Nonequilibrium response theory by Urna Basu (RRI, Bengaluru, India)
- Topology in statistical physics by Subhro Bhattacharjee (ICTS, Bengaluru, India)
- Statistical mechanics of developed turbulence by Nigel Goldenfeld (University of Illinois, Urbana-Champaign, US)
- Statistical physics of rare events and large deviations by Yariv Kafri (Technion -
Israel Institute of Technology, Haifa, Israel)
https://www.icts.res.in/program/bssp2020/talks
https://www.youtube.com/playlist?list=PL04QVxpjcnjjTv4rkFGzLa1PgRceIdtYO