Archive for Lugano

postdoc on COVID-19 modelling in Lugano

Posted in pictures, Statistics, Travel, University life with tags , , , , , , on July 24, 2021 by xi'an

A new call for postdoctoral applications from my friend Anto: a postdoctoral position is opening this Fall at the Università della Svizzera italiana (USI) in Lugano, Switzerland, under her direction, for conducting interdisciplinary approach to modelling the consequences of the COVID-19 pandemic and responses to it on other outcomes, such as mortality.

PRIMA grants in Lugano

Posted in Mountains, pictures, Travel, University life with tags , , , , on June 8, 2021 by xi'an

Forwarding a call from my friend Antonietta Mira for young female scientists to join her at USI, Lugano, Svizzera, for projects in Data Science, funded by a PRIMA PhD grant. Deadline is 1 September 2021.

Prima grants are aimed at young female researchers who wish to conduct, manage and lead an independent project at a Swiss higher education institution. It awards five-years grants to female researchers who fulfill the following criteria:

  • They match the SNSF requirements for Prima concerning academic age (mobility is not needed):  At least 2 years of research experience after the doctorate; Maximum 10 years from the doctorate.

  • They have an excellent academic track record, especially in terms of publications, and firm ambitions to pursue an academic career.

  • They demonstrate interest in scientific domains represented at USI.

indecent exposure

Posted in Statistics with tags , , , , , , , , , , , , on July 27, 2018 by xi'an

While attending my last session at MCqMC 2018, in Rennes, before taking a train back to Paris, I was confronted by this radical opinion upon our previous work with Matt Moores (Warwick) and other coauthors from QUT, where the speaker, Maksym Byshkin from Lugano, defended a new approach for maximum likelihood estimation using novel MCMC methods. Based on the point fixe equation characterising maximum likelihood estimators for exponential families, when theoretical and empirical moments of the natural statistic are equal. Using a Markov chain with stationary distribution the said exponential family, the fixed point equation can be turned into a zero divergence equation, requiring simulation of pseudo-data from the model, which depends on the unknown parameter. Breaking this circular argument, the authors note that simulating pseudo-data that reproduce the observed value of the sufficient statistic is enough. Which is related with Geyer and Thomson (1992) famous paper about Monte Carlo maximum likelihood estimation. From there I was and remain lost as I cannot see why a derivative of the expected divergence with respect to the parameter θ can be computed when this divergence is found by Monte Carlo rather than exhaustive enumeration. And later used in a stochastic gradient move on the parameter θ… Especially when the null divergence is imposed on the parameter. In any case, the final slide shows an application to a large image and an Ising model, solving the problem (?) in 140 seconds and suggesting indecency, when our much slower approach is intended to produce a complete posterior simulation in this context.

a Swiss summer school on data assimilation

Posted in Books, Kids, Mountains, pictures, Statistics, Travel, University life with tags , , , , , on May 14, 2018 by xi'an

My friend Antonietta Mira sent me the announcement of a combined summer school and workshop on “Data Assimilation” that will take place from September 11th to 15th in Lugano, Switzerland. With Tamara Broderick, Philippe Moireau, and Andrew Stuart as teachers. (Registration, incl. lunches, is 120 CHF for the whole week.)

Bayesian postdoc in Confœderatio Helvetica

Posted in Mountains, Statistics, Travel, University life with tags , , , , , , , , , on April 13, 2018 by xi'an

Antonietta Mira (Università della Svizzera italiana, Lugano) sent me this call for a postdoctoral position between Villigen, near Zürich, hence this picture) and Lugano:

Postdoctoral Fellow: Data Science/Bayesian Inference on Neutron Spectroscopy Data

Your tasks

The increasing availability of empirical large-scale neutron time-of-flight spectroscopy data and steady improvements in computational capacity have resulted in challenges as well as opportunities. This interdisciplinary SDSC-funded project “Bayesian parameter inference from stochastic models (BISTOM)” aims at developing statistical methods and software for analyzing 4D neutron spectroscopy data of quantum magnets. The project is co-directed by Prof. Dr A. Mira (Data Science Center at USI), Dr C. Albert (Eawag), and Prof. Dr Ch. Rüegg (PSI and Univ. Geneva).

Your profile

  • PhD in physics, statistics, applied mathematics or computer science
  • Solid background in neutron spectroscopy or computational statistics/Bayesian inference
  • Strong computational skills
  • Strong scientific writing and communication skills in English

Your working place will be PSI, Villigen and USI, Lugano.

We offer

Our institution is based on an interdisciplinary, innovative and dynamic collaboration. If you wish to optimally combine work and family life or other personal interests, we are able to support you with our modern employment conditions and the on-site infrastructure. Your employment contract is initially limited to 2 years, but may be extended up to 4 years in combination with other grants/fellowships e.g. Marie-Curie.

For further information please contact Prof. Dr Christian Rüegg, phone +41 56 310 47 78. Please submit your application online (including CV, list of publications and addresses of referees) for the position as a Postdoctoral Fellow (index no. 3004-00).