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PhD course STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS, Politecnico di Milano
by Luca Scarpa 26 Jan '23

26 Jan '23

Announcement: PhD Course on STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS by Dr. Luca Scarpa Lectures: 20/02, 27/02, 06/03, 13/03, 20/03, 27/03, 03/04, 12/04, 17/04 Location: Dipartimento di Matematica (III piano), Politecnico di Milano, Via Bonardi 9, Milano Enrolment information: https://www.dottorato.polimi.it/futuri-dottorandi/corsi-singoli Course webpage: https://www11.ceda.polimi.it/schedaincarico/schedaincarico/controller/sched… Best regards, Luca Scarpa ----- Luca Scarpa, PhD Tenure-Track Assistant Professor Department of Mathematics Politecnico di Milano Via E. Bonardi 9 20133 Milano, Italy e.mail: luca.scarpa(a)polimi.it url: https://sites.google.com/view/lucascarpa

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Ph.D. positions in "Physics-Informed or Theory-Driven machine learning" at the TU Chemnitz
by Imma Curato 25 Jan '23

25 Jan '23

Dear Colleagues, The department of Mathematics at the TU Chemnitz invites applications for two 3 years Ph.D. positions to work on projects in "Physics-informed or theory-guided machine learning." The deadline for the application is 10.02. More information on the call can be found in the link below. https://www.tu-chemnitz.de/verwaltung/personal/stellen/224034_1_LH.php Don't hesitate to write to imma.curato(a)uni-ulm.de<mailto:imma.curato@uni-ulm.de> for any position inquiries. Best Regards Imma Curato

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Postdoc position in Milano
by Stefania Ugolini 25 Jan '23

25 Jan '23

We recall the approaching deadline January 30-th 2023 of the postdoc position at the Department of Mathematics of Università degli Studi (Milano) entitled: Stochastic methods in quantum system Best regards, Stefania Ugolini. https://www.unimi.it/sites/default/files/2022-12/BANDO_tipo_A_2022BIS%20eng…

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RTDA SECS/S-01 Politecnico di Milano
by Laura Maria Sangalli 24 Jan '23

24 Jan '23

Con preghiera di massima diffusione a tutti i potenziali interessati. *** Nell'ambito del Progetto di Partenariato Esteso GRINS è appena stata bandita una posizione RTD-A nel settore SECS-S/01 sul tema Statistical Learning per il progetto GRINS - Growing Resilient, INclusive and Sustainable Scadenza: 13-02-23 Dettagli della procedura: bando<https://www.polimi.it/personale-docente/lavorare-al-politecnico/bandi-e-con…> L’attività di ricerca verterà sullo sviluppo di modelli statistici per la previsione ex-ante e la valutazione ex-post dell'impatto degli investimenti in infrastrutture e servizi per migliorare l'accessibilità, la resilienza e la sostenibilità dei territori e delle città (WP2 Progetto GRINS – PNRR PE9 Spoke7). Sarà necessario comprendere come i fattori tangibili (infrastrutture e infostrutture) interagiscono con quelli intangibili (coesione e inclusione sociali, mobilità,…) per definire la sostenibilità di un territorio e a) identificare gli elementi funzionali a rendere i territori accessibili; b) individuare i gap territoriali e che limitano la sostenibilità e c) definire e valutare politiche per colmare tali gap. Sono richieste competenze avanzate di Statistical Learning e Analisi Dati, e comprovata conoscenza di Data Management e programmazione (R, Python). Il ruolo prevede lo svolgimento di attività didattica. Per informazioni: Prof. Francesca Ieva – francesca.ieva(a)polimi.it<mailto:francesca.ieva@polimi.it> —— Laura Maria Sangalli MOX - Dipartimento di Matematica Politecnico di Milano Piazza Leonardo da Vinci 32 20133 Milano - Italy (+39) 02 2399 4554 laura.sangalli(a)polimi.it<mailto:laura.sangalli@polimi.it> https://sangalli.faculty.polimi.it

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Seminario Prof. E. Ronchetti
by Enea Bongiorno 24 Jan '23

24 Jan '23

Buongiorno, con piacere segnalo il seguente seminario: -------------------------------- 31 gennaio ore 16.30 - aula 101, campus Perrone, via Perrone, 18, Novara. Università del Piemonte Orientale. - on-line: meet.google.com/yvq-ccbt-pzt Title: *An Introduction to Saddlepoint Approximations* *Prof. Elvezio Ronchetti* Research Center for Statistics and Geneva School of Economics and Management University of Geneva, Switzerland Elvezio.Ronchetti(a)unige.ch www.unige.ch/gsem/en/research/faculty/honorary-professors/elvezio-ronchetti/ Abstract: Classical inference in statistics is typically carried out by means of standard (first-order) asymptotic theory. However, the asymptotic distribution of estimators and test statistics can provide a poor approximation of tail areas especially when the sample size is moderate to small. This can lead to inaccurate p-values and confidence intervals. Several techniques, both parametric and nonparametric, have been devised to improve first-order asymptotic approximations, including e.g. Edgeworth expansions, Bartlett's corrections, and bootstrap methods. Here we focus on saddlepoint techniques, introduced into statistics by H. Daniels, and more generally on small sample asymptotic techniques, an expression coined by F. Hampel to express the spirit of these methods. Indeed they provide very accurate approximations of tail probabilities down to small sample sizes and /or out in the tails. Moreover, these approximations exhibit a relative error of order 1/n, an improvement with respect to other available approximations obtained by means of Edgeworth expansions and similar techniques. We will review the basic ideas, show the link with other nonparametric methods such as empirical likelihood, and outline some connections to information theory and optimal transportation. ----------------------------------- Locandina dell'evento <https://drive.google.com/file/d/1INut-6sD210FwZ437k3ydQA5P3xchdIr/view?usp=…> Seminari Matematici Statistici <https://sites.google.com/uniupo.it/seminari-ms/home-page> ----------------------------------- Tutti gli interessati sono invitati a partecipare. Cordiali saluti, Enea -- Enea Bongiorno,PhD Associate Professor of Statistics Università degli Studi del Piemonte Orientale Via Perrone 18, 28100, Novara, Italia Phone: +390321375317 enea.bongiorno(a)uniupo.it upobook.uniupo.it/enea.bongiorno

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Seminar Fabio Spizzichino in Bologna
by Sabrina Mulinacci 23 Jan '23

23 Jan '23

Dear all, we are glad to announce the following hybrid seminar: Speaker: Fabio Spizzichino Title: Minima among subsets of random variables, Random permutations, and Load-sharing survival models Thursday, January 26, 2023 at 4 pm In person: Aula III - Department of Statistical Sciences, Via Belle Arti, 41, Bologna Teams Link: Fai clic qui per partecipare alla riunione<https://teams.microsoft.com/l/meetup-join/19%3ameeting_OTczODg3MjgtNzFkOC00…> ID riunione: 369 287 907 78 Passcode: yd7Kf2 The abstract and more details can be found here https://stat.unibo.it/it/eventi/minima-among-subsets-of-random-variables-ra… [https://stat.unibo.it/@@site-logo/logo-unibo.png]<https://stat.unibo.it/it/eventi/minima-among-subsets-of-random-variables-ra…> Minima among subsets of random variables, Random permutations, and Load-sharing survival models — Scienze Statistiche "Paolo Fortunati" - stat.unibo.it<https://stat.unibo.it/it/eventi/minima-among-subsets-of-random-variables-ra…> Relatore: Fabio Spizzichino (Università Sapienza) Tu sei qui: Home; Eventi; Minima among subsets of random variables, Random permutations, and Load-sharing survival models stat.unibo.it Please, do not hesitate to contact me for anything. Sincerely, Sabrina Mulinacci

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Seminar Klopp @Bocconi
by Giacomo Zanella 23 Jan '23

23 Jan '23

We announce the following seminar (held only in person): 26/01/2023 at 12:00 Bocconi University, Via Roentgen 1, Milan Room 3-B3-sr01, floor 3 Speaker: Olga Klopp (ESSEC and CREST). Personal webapge: http://kloppolga.perso.math.cnrs.fr/ Title: Optimality of Variational Inference for Stochastic Block Model Abstract: Variational methods are extremely popular in the analysis of network data. Statistical guarantees obtained for these methods typically provide asymptotic normality for the problem of estimation of global model parameters under the stochastic block model. In the present work, we consider the case of networks with missing links that is important in application and show that the variational approximation to the maximum likelihood estimator converges at the minimax rate. This provides the first minimax optimal and tractable estimator for the problem of parameter estimation for the stochastic block model. We complement our results with numerical studies of simulated and real networks, which confirm the advantages of this estimator over current methods. See also https://bidsa.unibocconi.eu/newsevents/bidsa-seminar-series-optimality-vari… . Best regards, Giacomo Zanella

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2nd Level Executive Master in QUANTUM MACHINE LEARNING
by Marco Corazza 23 Jan '23

23 Jan '23

*2nd LEVEL **EXECUTIVE ** MASTER in* *QUANTUM MACHINE LEARNING* (*https://www.cafoscarichallengeschool.it/.../quantum.../* <https://www.cafoscarichallengeschool.it/master/quantum-machine-learning/?fb…> ) Dear All, I'm informing you that: - the deadline for the enrollment to the *EXECUTIVE 2nd LEVEL MASTER in QUANTUM MACHINE LEARNING* is approaching: February 1, 2023, *- 5 INPS full-coverage scholarships are available for Italian civil servants (https://www.inps.it/Welfare/default.aspx?lastMenu=21556... <https://www.inps.it/Welfare/default.aspx?lastMenu=21556&iMenu=1&tb=0&fondo=…>).* for any information, you can contact lorenzo.paolini(a)unive.it. Regards, Marco Corazza P.S. - Please, give wide diffusion to this announcement. -- Marco Corazza, Ph.D. Department of Economics - Ca' Foscari University of Venice San Giobbe, Cannaregio 873 - 30121 Venezia, Italy Mobile: (+39) 366 602-9134 Phone: (+39) 041 234-6921 Fax: (+39) 041 234-7444 E-mail: corazza(a)unive.it Editor-in-Chief: Mathematical Methods in Economics and Finance - www.unive.it/m2ef

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Phd In Statistics & Computer Science - scadenza domande
by Antonio Lijoi 23 Jan '23

23 Jan '23

Care/i tutte/i, ricordo che la scadenza per la presentazione delle domande di ammissione al dottorato in Statistics and Computer Science dell’Università Bocconi, Milano, è imminente: 1 Febbraio. Vi sarei molto grato se voleste portare all'attenzione di vostri studenti interessati l'annuncio riportato di seguito. Saluti e buona settimana, AL ******************* PhD in Statistics and Computer Science - a.y. 2023-2024 Call for applications for PhD student positions ******************* The Bocconi PhD School provides 7 scholarships for the PhD in Statistics and Computer Science, and a position with tuition waiver. * Scholarship amount * 20,000 euros per annum Further funding may be available through teaching and research assistantship. Visit www.unibocconi.eu/admissionphd for detailed information. ** Applications are due by February 1, 2023 ** Within the PhD School at Bocconi University, the four-year PhD program in Statistics and Computer Science is a high profile and rigorous doctoral program that develops strong mathematical, statistical, computational and programming backgrounds. The curriculum is structured into two tracks: Statistics and Computer Science. The first year includes courses that are compulsory for all enrolled PhD students. The second-year features track-specific and elective courses that provide students with a more specialized competence and focus on topics that may be the object of the doctoral dissertation. Dedicated mentorship is offered to students throughout their time at Bocconi. Multidisciplinary interchange with other graduate programs in Bocconi’s PhD School, as well as research experience abroad, are also encouraged. The Faculty includes internationally acknowledged top researchers in Statistics, Computer Science, Machine Learning, Decision Theory and Statistical Physics. The program also benefits from contributions of authoritative visiting professors who deliver short monographic courses. Highly qualified and motivated students with M.Sc. degrees in Statistics, Mathematics, Computer Science, Economics, Physics, Engineering and related areas, as well as other quantitatively-oriented fields, are encouraged to apply for admission. Applicants should hold, or be on their way to hold, a graduate degree or equivalent. For further information about the PhD program in Statistics and Computer Science at Bocconi, visit www.unibocconi.eu/phdstatscompscience and feel free to contact: Antonio Lijoi (antonio.lijoi(a)unibocconi.it) Angela Baldassarre, PhD administrative assistant (angela.baldassarre(a)unibocconi.it) Antonio Lijoi ----- Bocconi University http://mypage.unibocconi.eu/antoniolijoi

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Call of interest at U. Venice (open position in Statistics or Math for Social Sciences)
by Marco LI CALZI 20 Jan '23

20 Jan '23

The Department of Management at U. Ca’ Foscari Venezia is interested in receiving expressions of interest for a position in Statistics, or in Mathematics Applied to Social Sciences. The position is open (tenure-track, associate, or full). Scholars with three years’ of seniority abroad may be hired directly. Candidates should have a solid knowledge of advanced mathematical tools and their research output should have used them in at least one of the following areas: management science, economics, finance, insurance, decision theory, game theory, or social sciences. Emphasis on data science or network science is particularly appreciated. Please address questions or inquiries to Marco Li Calzi <licalzi(a)unive.it <mailto:licalzi@unive.it>>. __________________________________ Marco Li Calzi Department of Management Università Ca' Foscari Venezia San Giobbe, Cannaregio 873 30121 Venezia, Italy T. +39 041 234 6925 M. licalzi(a)unive.it WWW: http://mizar.unive.it/licalzi

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