The Department of Statistics and Data Science at Carnegie Mellon University invites applicants for a two-year #postdoc fellowship in simulation-based inference. The fellow will work with Prof. Cosma Shalizi of the department on developing theory, algorithms and applications of random feature methods in simulation-based inference, with a particular emphasis on social-scientific problems connected to the work of CMU's Institute for Complex Social Dynamics. Apart from by the supervisor, the fellow will also be mentored by other faculty in the department and the ICSD, depending on their interests and secondary projects, and will get individualized training in both technical and non-technical professional skills.
Successful applicants will have completed a Ph.D. in Statistics, or a related quantitative discipline, by September 2025, and ideally have a strong background in non-convex and stochastic optimization and/or Monte Carlo methods, and good programming and communication skills. Prior familiarity with simulation-based inference, social network models and agent-based modeling will be helpful, but not necessary.
The Department of Statistics and Data Science at Carnegie Mellon University invites applicants for a two-year #postdoc fellowship in simulation-based inference. The fellow will work with Prof. Cosma Shalizi of the department on developing theory, algorithms and applications of random feature methods in simulation-based inference, with a particular emphasis on social-scientific problems connected to the work of CMU's Institute for Complex Social Dynamics. Apart from by the supervisor, the fellow will also be mentored by other faculty in the department and the ICSD, depending on their interests and secondary projects, and will get individualized training in both technical and non-technical professional skills.
Successful applicants will have completed a Ph.D. in Statistics, or a related quantitative discipline, by September 2025, and ideally have a strong background in non-convex and stochastic optimization and/or Monte Carlo methods, and good programming and communication skills. Prior familiarity with simulation-based inference, social network models and agent-based modeling will be helpful, but not necessary.
"Your messages about the movement of the enemy through the official chatbot … bring new trophies every day," the government agency tweeted. Telegram boasts 500 million users, who share information individually and in groups in relative security. But Telegram's use as a one-way broadcast channel — which followers can join but not reply to — means content from inauthentic accounts can easily reach large, captive and eager audiences. At its heart, Telegram is little more than a messaging app like WhatsApp or Signal. But it also offers open channels that enable a single user, or a group of users, to communicate with large numbers in a method similar to a Twitter account. This has proven to be both a blessing and a curse for Telegram and its users, since these channels can be used for both good and ill. Right now, as Wired reports, the app is a key way for Ukrainians to receive updates from the government during the invasion. As such, the SC would like to remind investors to always exercise caution when evaluating investment opportunities, especially those promising unrealistically high returns with little or no risk. Investors should also never deposit money into someone’s personal bank account if instructed. "The inflation fire was already hot and now with war-driven inflation added to the mix, it will grow even hotter, setting off a scramble by the world’s central banks to pull back their stimulus earlier than expected," Chris Rupkey, chief economist at FWDBONDS, wrote in an email. "A spike in inflation rates has preceded economic recessions historically and this time prices have soared to levels that once again pose a threat to growth."
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