Master of Science program in Social Data Science (MS SDS)

The program will provide US and Austrian degrees simultaneously to educate the future generations of data scientists sensitive to social problems.

https://networkdatascience.ceu.edu/msc-social-data-science

Two threads on calcalus in non-integer dimensions and how it is used in Quantum Field Theory

https://twitter.com/martinmbauer/status/1579221233593651200

Two open #PhD positions in Sustainability and Complex Systems with us. They may be assigned to any of seven predefined but very broad research areas including transport, energy system modeling, sustainable transitions, sustainable consumption, land use, etc

https://www.chalmers.se/en/about-chalmers/Working-at-Chalmers/Vacancies/Pages/default.aspx?rmpage=job&rmjob=10996&rmlang=UK

The international #internship program, CaCTüS, offers paid research internships at the #Max_Planck_Institute for Biological Cybernetics, the Max Planck Institute for Intelligent Systems and the AI Center in Tübingen & Stuttgart (Germany) to students who face significant constraints in their pursuit of a career in AI or brain research.

 
About the CaCTüS Internship program
cactus-internship.tuebingen.mpg.de
 
The sciences of biological and artificial intelligence are rapidly growing research fields that need enthusiastic minds with a keen interest in solving challenging questions. The Max Planck Institutes for Biological Cybernetics and Intelligent Systems as well as the AI Center in Tübingen & Stuttgart (Germany) offer up to 10 students at the Bachelor or Master level paid three-months internships during the summer of 2023. Successful applicants will work with top-level scientists on research projects spanning machine learning, electrical engineering, theoretical neuroscience, behavioral experiments and data analysis. The CaCTüS Internship is aimed at young scientists who are held back by personal, financial, regional or societal constraints to help them develop their research careers and gain access to first-class education. The program is designed to foster inclusion, diversity, equity and access to excellent scientific facilities. We specifically encourage applications from students living in low- and middle-income countries which are currently underrepresented in the Max Planck Society research community.
 
Application deadline: 4 December 2022

"Martingales for Physicists" (by Édgar Roldán, Izaak Neri, Raphael Chetrite, Shamik Gupta, Simone Pigolotti, Frank Jülicher, Ken Sekimoto): arxiv.org/abs/2210.09983

"We review the theory of martingales as applied to stochastic thermodynamics and stochastic processes in physics more generally."

#PhD and #Postdoc Researcher positions (f/m/d) | Nonequilibrium statistical physics of active matter and living systems - GÖTTINGEN

https://www.mpg.de/19382858/postdoctoral-researcher-positions1

New #PhD-position open in the Department Living Matter Physics! If you like working in an interdisciplinary & international team, this might be a great opportunity for you.

https://jobs.b-ite.com/jobposting/c6995bd5180383bebb2fd79f0e635b7562b832400

There is a new opportunity for a fully-funded 4-year #PhD position in "agent-based modelling of urban economic segregation" BKTUDelft!

Looking for a curious individual with skills and an interest in computational and social science. This curious individual's task will be to solve challenges of building a large modular #ABM from reusable building blocks representing complementary and alternative #theories of economic #inequality and #segregation and using empirical #microdata from initialisation & evaluation.

Please apply online by 21st November 2022.

TWO #postdoc positions in my group at CSAalto. Come work with me on network science & computational social science topics within new projects related to polarisation in societies, misinformation & coordinated activities on social media.

See mkivela.com/postdoc/

Epidemic Models with Manual and Digital Contact Tracing
Tom Britton (Stockholm University/Simons Institute)

https://youtu.be/nOjE4vTTotg?list=PLgKuh-lKre12ZMiI5-myvjGfAPlndYSNh

Algorithms Using Local Graph Features to Predict Epidemics
Yeganeh Alimohammadi (Stanford)

People's interaction networks play a critical role in epidemics. However, precise mapping of the network structure is often expensive or even impossible. I will show that it is unnecessary to map the entire network. Instead, contact tracing a few samples from the population is enough to estimate an outbreak's likelihood and size.

More precisely, I start by studying a simple epidemic model where one node is initially infected, and an infected node transmits the disease to its neighbors independently with probability p. In this model, I will present a nonparametric estimator on the likelihood of an outbreak based on local graph features and give theoretical guarantees on the estimator's accuracy for a large class of networks. Finally, I will extend the result to the general SIR model with random recovery time: Local graph features are enough to predict the time evolution of epidemics on a large class of networks.

https://youtu.be/pOrEESEluxU

Mathematics of the COVID-19 Pandemics: Lessons Learned and How to Mitigate the Next One
Abba Gumel (University of Maryland)

The novel coronavirus that emerged in December 2019, COVID-19, is the greatest public health challenge humans have faced since the 1918 influenza pandemic (it has so far caused over 615 million confirmed cases and 6.5 million deaths). In this talk, I will present some mathematical models for assessing the population-level impact of the various intervention strategies (pharmaceutical and non-pharmaceutical) being used to control and mitigate the burden of the pandemic. Continued human interference with the natural ecosystems, such as through anthropogenic climate change, environmental degradation, and land use changes, make us increasingly vulnerable to the emergence, re-emergence and resurgence of infectious diseases (particularly respiratory pathogens with pandemic potential). I will discuss some of the lessons learned from our COVID-19 modeling studies and propose ways to mitigate the next respiratory pandemic.

https://youtu.be/KakzvrQf_CA

Complex Contagions and Hybrid Phase Transitions
Joel Miller (La Trobe University)

A complex contagion is an infectious process in which individuals may require multiple transmissions before changing state. These are used to model behaviours if an individual only adopts a particular behaviour after perceiving a consensus among others. We may think of individuals as beginning inactive and becoming active once they are contacted by a sufficient number of active partners. Here we study the dynamics of the Watts threshold model (WTM). We adapt techniques developed for infectious disease modelling to develop an analyse analytic models for the dynamics of the WTM in configuration model networks and a class of random clustered (triangle-based) networks. We derive conditions under which cascades happen with an arbitrarily small initial proportion active. We also observe hybrid phase transitions when cascades are not possible for small initial conditions, but occur for large enough initial conditions.

https://youtu.be/17QkYHxDaAY

Testing, Voluntary Social Distancing, and the Spread of an Infection
Ali Makhdoumi (Duke University)

In this talk, we present a modeling framework to study the effects of testing policy on voluntary social distancing and the spread of an infection. Agents decide their social activity level, which determines the social network over which the virus spreads. Testing enables the isolation of infected individuals, slowing down the infection. But greater testing also reduces voluntary social distancing or increases social activity, exacerbating the spread of the virus. We show that the effect of testing on infections is non-monotone. This non-monotonicity also implies that the optimal testing policy may leave some of the testing capacity of society unused. This also implies that testing should be combined with mandatory social distancing measures to avoid these adverse behavioral effects.

https://youtu.be/YEOnmfold74

Looking for a #PhD on comp. soc. science and/or net science? Get in touch! Topics include (many aspects of) cryptos/nfts/blockchain, social nets, misinformation, modelling of massive nets, etc. Lots of data, great team and close collab. with private and public organisations.

https://www.andreabaronchelli.com/

#PhD student in social data science

The student will join the Uppsala University Information Laboratory (https://uuinfolab.github.io). This project studies the role of images in the spread and anchoring of political ideas, and ultimately how visual politics contributes to persuasion and shaping the political agenda. Visual politics is increasingly prominent in digital public spaces, where image-based (dis)information spreads effectively. We know that images are a powerful form of political communication, that visual communication is perceived as convincing and affects people's perceptions of a variety of issues. At the same time, we still know surprisingly little about the actors who use images to promote political ideas, what mechanisms are at play, and even less what impact these activities have on public discourse. Your role in the project will be to develop and apply social data science research methods and methodologies that are suitable for analysing large-scale and complex visual spreading phenomena.

https://www.uu.se/en/about-uu/join-us/details/?positionId=561864

MSc Programme in "Social Data Science" at University College Dublin is now open for application.
The 1-year programme (2-years part-time) provides sociological thinking combined with data science skills.
https://lnkd.in/eVKmsGGh

Fully-funded #PhD scholarships are available with our CRT commencing in Sept 2023. Join 113 students & begin your 4-year PhD journey with us.
https://data-science.ie/how-do-i-apply/