Archive for bois de Boulogne

postdoc shortage

Posted in Books, pictures, Statistics, Travel, University life with tags , , , , , , , , , on October 4, 2022 by xi'an

An interesting tribune in Nature (30 August) about the difficulty in hiring postdocs… I myself faced this difficulty in the recent years but though it was mostly due to unattractive French salaries and working conditions, or COVID issues (or myself!). Nature mentions politics, economics, ethics, and personal priorities as main reasons for the postdoctoral drought. In Britain, Brexit is definitely a central factor as candidates face enormous bills to secure entry to the United Kingdom (as Hai-Dang Dau, now in Oxford, was explaining to us after his successful PhD defense at ENSAE-CREST this morning). But more globally this may reflect a general exodus from academia towards company jobs, and their much more attractive salaries. Especially in STEM where Amazon and buddies created a new definition of “dream jobs”… Anyway,  I still have a prAirie postdoc position open in Paris Dauphine and the new PariSanté campus provides a great working environment, so feel free to contact me!

course PSL 2020

Posted in Running, University life with tags , , , , , on March 14, 2020 by xi'an

Irène Waldspurger, CNRS bronze medal

Posted in Statistics with tags , , , , , , on February 14, 2020 by xi'an

My colleague at Paris Dauphine, Irène Waldspurger, got one of the prestigious CNRS bronze medals this year. Irène is working on inverse problems and machine learning, with applications to sensing and imaging. Congrats!

ABC with Gibbs steps

Posted in Statistics with tags , , , , , , , , , , , , , , , , , on June 3, 2019 by xi'an

With Grégoire Clarté, Robin Ryder and Julien Stoehr, all from Paris-Dauphine, we have just arXived a paper on the specifics of ABC-Gibbs, which is a version of ABC where the generic ABC accept-reject step is replaced by a sequence of n conditional ABC accept-reject steps, each aiming at an ABC version of a conditional distribution extracted from the joint and intractable target. Hence an ABC version of the standard Gibbs sampler. What makes it so special is that each conditional can (and should) be conditioning on a different statistic in order to decrease the dimension of this statistic, ideally down to the dimension of the corresponding component of the parameter. This successfully bypasses the curse of dimensionality but immediately meets with two difficulties. The first one is that the resulting sequence of conditionals is not coherent, since it is not a Gibbs sampler on the ABC target. The conditionals are thus incompatible and therefore convergence of the associated Markov chain becomes an issue. We produce sufficient conditions for the Gibbs sampler to converge to a stationary distribution using incompatible conditionals. The second problem is then that, provided it exists, the limiting and also intractable distribution does not enjoy a Bayesian interpretation, hence may fail to be justified from an inferential viewpoint. We however succeed in producing a version of ABC-Gibbs in a hierarchical model where the limiting distribution can be explicited and even better can be weighted towards recovering the original target. (At least with limiting zero tolerance.)

postdoc position still open

Posted in pictures, Statistics, University life with tags , , , , , , , , , , , , , , on May 30, 2019 by xi'an

The post-doctoral position supported by the ANR funding of our Paris-Saclay-Montpellier research conglomerate on approximate Bayesian inference and computation remains open for the time being. We are more particularly looking for candidates with a strong background in mathematical statistics, esp. Bayesian non-parametrics, towards the analysis of the limiting behaviour of approximate Bayesian inference. Candidates should email me (gmail address: bayesianstatistics) with a detailed vita (CV) and a motivation letter including a research plan. Letters of recommendation may also be emailed to the same address.

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