August 2026 - Random - Mailing list — Dipartimento di Matematica, UniPI

PhD position in Mathematical Foundations of Machine Learning at University of Bern
by Andrea Agazzi 14 Aug '26

14 Aug '26

Dear Colleagues, The Department of Mathematics and Statistics of the University of Bern is seeking an excellent candidate for a PhD position in the area of Mathematical Foundations of Machine Learning under my supervision with an expected starting date in Fall Semester 2026, or by agreement (we are quite flexible). For further details concerning the position, application procedure, salary, and eligibility requirements, please follow this link: https://jobs.unibe.ch/job-vacancies/phd-position-in-mathematical-foundation… Review of applications will begin in the *last week of August 2026* and continue until the position is filled. I would be grateful if you could circulate this announcement to potential candidates. Best wishes, Andrea Agazzi (andrea.agazzi(a)unibe.ch)

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PhD/Postdoc position - Ruhr University Bochum
by Nicola Turchi 13 Aug '26

13 Aug '26

Dear colleagues, I am pleased to share the following call for applications. Please feel free to circulate this within your networks. __________ PhD or Postdoctoral Position in Probability Theory *Ruhr University Bochum – Faculty of Mathematics* *Application deadline: September 1, 2026* The Faculty of Mathematics at Ruhr University Bochum invites applications for a PhD or Postdoctoral position in Probability Theory. The starting date is flexible, but preferably no later than January 2027. The position is part of the research group of Prof. Christoph Thäle, which focuses on stochastic geometry and geometric probability. The group studies the asymptotic behavior of random spatial structures, ranging from discrete to high-dimensional models, using methods from probability theory and geometric analysis. We are looking for a highly motivated candidate who wishes to conduct independent research in a modern area of probability theory, ideally with a focus on stochastic geometry. Applicants should hold an excellent Master’s degree (for the PhD position) or PhD (for the Postdoctoral position) in mathematics, preferably in one of the following areas: - Probability theory - Geometry - Combinatorics *Position details:* - *PhD position:* 75% TV-L E13 (German public sector pay scale), fixed term of three years - *Postdoctoral position:* 100% TV-L E13, fixed term of two years *Application process:* Interested candidates should contact Tanja Schiffmann at tanja.schiffmann(a)rub.de to obtain the link to the online application portal. Applications must be submitted through the portal as a single PDF file containing: - a cover letter - a curriculum vitae - academic transcripts All application materials must be received by *September 1, 2026*. For academic inquiries, please contact Christoph Thäle or visit his website <https://sites.google.com/view/christophthaele/start>. __________ Best regards, Nicola Turchi Dipartimento di Matematica e Applicazioni Università degli Studi di Milano-Bicocca

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PhD position in Numerical Analysis at Bielefeld University - Deadline: AUGUST 19
by Ferrari, Giorgio 12 Aug '26

12 Aug '26

Dear All, I forward with pleasure the announcement for a PhD position in Numerical Analysis at Bielefeld University: https://jobs.uni-bielefeld.de/jobpdfprint/4927 Best wishes, Giorgio Ferrari

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Seminario Fabio Centofanti, KU Leuven, presso Politecnico di Milano
by Laura Maria Sangalli 08 Aug '26

08 Aug '26

Cari Colleghi, A seguire annuncio di un seminario organizzato presso il Laboratorio MOX - Dipartimento di Matematica, Politecnico di Milano Fabio Centofanti, KU Leuven, Belgium 11.09.26 ore 14:00 – Aula Saleri, sesto piano Dipartimento di Matematica Titolo: Robust Multivariate Analysis under Cellwise and Casewise Contamination Abstract: Robust statistics has traditionally focused on casewise outliers, meaning observations that behave differently from the bulk of the data. In modern datasets, however, contamination can occur in the form of cellwise outliers, which are individual contaminated entries in the data matrix. Even when the proportion of contaminated cells is relatively small, many observations may still contain at least one outlying value, which can make both classical and casewise robust methods unreliable. This talk presents recent developments for handling situations in which casewise and cellwise outliers appear simultaneously. We begin by introducing cellPCA, a novel robust principal component analysis method that estimates the principal subspace while simultaneously accommodating cellwise and casewise outliers, as well as missing values. Building on cellPCA, we then introduce cellRCov, which is a robust covariance estimator for high dimensional settings. The second part of the talk focuses on multivariate linear regression. The cellMR estimator combines robust covariance estimation with regularization to handle outliers in both the predictor and response matrices. We then introduce cellBoot, a bootstrap procedure based on indirect inference that complements robust estimation with valid confidence intervals for the regression coefficients. We conclude with a perspective on more complex data structures and contamination patterns, including tensor data, time series, functional data, and blockwise contamination. Un caro saluto a tutti, Laura Sangalli —— 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 https://sangalli.faculty.polimi.it

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