Buongiorno,
invio notizia di 2 posizioni Postdoc all'Università di Granada su
argomenti:
- "Modelling and differential equations" e "Statistics and operational
research".
_____________________________________________________________
To all interested candidates:
The Institute of Mathematics of the University of Granada (IMAG) offers two
postdoctoral positions, to start in September-October 2024, and with an end
date of December 31, 2025. These positions are in the areas of "*Modelling
and differential equations*" and "*Statistics and operational research*"
(one position per area). The application deadline is *June 10, 2024*.
Further details can be found at IMAG's website
https://wpd.ugr.es/~imag/imag-maria-de-maeztu-postdocs-2024/
These contracts are supported by IMAG's Excellence Seal "María de Maeztu"
with reference CEX2020-001105-M.
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Dear colleague,
the Technical University of Vienna is advertising a 6-year assistant professor position (non-tenured) in probability theory, within the Probability research group (https://www.tuwien.at/en/mg/proba)<https://www.tuwien.at/en/mg/mstoch>
<https://www.tuwien.at/en/mg/mstoch>
Deadline for applications: June 27th, 2024. Earliest possible starting date: September 2024
For the official announcement, the link to the application portal and details on the position, see here: https://jobs.tuwien.ac.at/Job/233239
The teaching load is 4 hours/week.
Please forward this to potentially interested candidates
Best wishes
Fabio Toninelli (head of the Probability group)
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Prof. Fabio Toninelli
Technical University of Vienna
Institut für Stochastik und Wirtschaftsmathematik
Wiedner Hauptstrasse 8-10, 1040 Wien, Austria
https://sites.google.com/view/fabio-toninelli/home
Office: 6th floor, green area. tel: +43-1-58801-10570
Dear All,
this is to inform about an open Postdoc position at the department of Statistics and Operations Research at the University of Vienna, in the working group of Prof. Cuchiero.
The University of Vienna, Department of Statistics and Operations Research, invites applications for the position of a Post-Doc (2 years, 40h) at the intersection of Mathematical Finance, Stochastic Analysis and Machine Learning. The post-doctoral researcher will work in the group of the START research project "Universal structures in Mathematical Finance", led by Prof. Christa Cuchiero. The focus of the project lies on universal structures that pertain literally to both, mathematics and finance.
*Deadline for applications: June 15, 2024.*
Further information can be found here:
https://jobs.univie.ac.at/job-invite/2493/
Please foward this message to any interested person.
Thank you and best wishes
Viktoria Schildhammer
Dear All,
this is to inform about an open Praedoc position at the department of Statistics and Operations Research at the University of Vienna, in the working group of Prof. Cuchiero.
The University of Vienna, Department of Statistics and Operations Research, invites applicants for the position of one to two Prae-Docs (3 year appointment, 30 hours) at the intersection of Mathematical Finance, Stochastic Analysis and Machine Learning.
The pre-doctoral researcher will work in the group of the START research project "Universal structures in Mathematical Finance", led by Prof. Christa Cuchiero. The focus of the project lies on universal structures that pertain literally to both, mathematics and finance
*Deadline for applications: June 15, 2024.*
Further information can be found here:
https://jobs.univie.ac.at/job-invite/2491/
Please foward this message to any interested person.
Thank you and best wishes
Viktoria Schildhammer
Dear All,
this is to inform about a *3-year post-doctoral position* in my group at
the Center for Mathematical Economics of Bielefeld University (salary
level TVL-13, 100%).
The post-doctoral researcher will conduct research on stochastic games
(with N players or of mean-field type) wiith singular controls, as well
as on mean-field control problems.
*Deadline for applications: June 12, 2024.*
Further information can be found here:
https://jobs.uni-bielefeld.de/job/view/3392/research-position-postdoc?page_…
Please foward this message to any interested person.
Best wishes and thanks,
Giorgio Ferrari
Carissimi colleghi,
scusandomi per eventuali invii multipli, vi inoltro il seguente annuncio di
seminario.
Tutti gli interessati sono invitati a partecipare.
Cordialmente,
Enea Bongiorno
--------------------------------
- data e orario: 23 maggio 2024 ore 15.00
- aula 204, campus Perrone, via Perrone, 18, Novara. Università del
Piemonte Orientale.
- on-line: meet.google.com/iap-gjcr-bkb
Title: *Regression analysis with density functions in Bayes spaces*
*Ivana Pavlů*, Palacký University Olomouc, Czech Republic
*Abstract*:
Regression analysis offers tools for explaining the relation between (a set
of) dependent and independent variables. Recent advances extend the
available response types from uni- or multivariate to functional, and more
recently also distributional responses. For functional distributions, often
represented through probability density functions, the Bayes space
framework was developed to respect the relative information they carry. The
Hilbert space structure of Bayes space enables one to utilize standard
methods of functional data analysis for the use on - properly transformed -
density functions. Focusing on regression analysis, it is possible to
construct adequate models with densities on the side of both the dependent
and independent variables.
In this seminar, a brief overview of regression models for univariate
densities will be presented. A closer attention will be given to the
possible generalization of additive regression model for bivariate
distributions. Finally, an outlook at the Bayesian inference in linear
regression with probability densities will be discussed. All proposed
methods will be demonstrated on real data from the fields of geochemistry
and demographics.
-----------------------------------
Locandina dell'evento
<https://drive.google.com/file/d/1AW4P1_HNdVO7Ot70mjM-KCQLhnSSVmRi/view?usp=…>
Seminari Matematici Statistici <https://seminari-ms.uniupo.it/home-page>
-----------------------------------
--
Enea G. Bongiorno,
Università degli Studi del Piemonte Orientale - Amedeo Avogadro
Via Perrone 18, 28100, Novara, Italia
Phone: +390321375317
enea.bongiorno(a)uniupo.it
upobook.uniupo.it/enea.bongiorno
------
Math-Stat Seminars at UPO
seminari-ms.uniupo.it/home-page
------
Dear all,
you are all invited to participate to the following seminar.
Speaker : Domenico Marinucci (https://sites.google.com/view/domenicomarinucci/home)
Affiliation: Dipartimento di Matematica - Università Roma Tor Vergata
Title: Spectral complexity of deep neural networks
Date: Monday, May 29, 2024 at 11.30
Place: Aula 704 (7th floor) , Dipartimento di Matematica at University of Genova, Via Dodencaneso 35,
Abstract: It is well-known that randomly initialized, push-forward,
fully-connected neural networks weakly converge to isotropic Gaussian
processes, in the limit where the width of all layers goes to infinity.
In this paper, we propose to use the angular power spectrum of the
limiting fields to characterize the complexity of the network
architecture. In particular, we define sequences of random variables
associated with the angular power spectrum, and provide a full
characterization of the network complexity in terms of the asymptotic
distribution of these sequences as the depth diverges. On this basis, we
classify neural networks as low-disorder, sparse, or high-disorder; we
show how this classification highlights a number of distinct features
for standard activation functions, and in particular, sparsity
properties of ReLU networks. Our theoretical results are also validated
by numerical simulations.
Joint work with Simmaco Di Lillo, Michele Salvi e Stefano Vigogna
Best wishes,
Ernesto
---------------------
Ernesto De Vito
DIMA - Dipartimento di Matematica
MaLGa - Machine Learning Genoa center
Via Dodecaneso 35
16146 Genova
Italy
e-mail: ernesto.devito(a)unige.it
tel: +390103536783
Cari tutti,
ho appena pubblicato il seguente bando per un assegno di ricerca di 15 mesi all’università di Bologna su un progetto in collaborazione con Fincantieri (https://www.fincantieri.com/it/) riguardante simulazioni numeriche di algoritmi quantistici per le equazioni di Navier-Stokes:
https://bandi.unibo.it/ricerca/assegni-ricerca?id_bando=67830
L’assegno prevede uno stipendio competitivo di circa 2000€ netti al mese. È richiesta solo la laurea magistrale, ma un’esperienza in simulazioni numeriche di algoritmi quantistici è preferibile. I candidati possono allegare alla domanda fino a due lettere di referenza. La presa di servizio è prevista per il 1° giugno, e la scadenza del bando è il 21 aprile.
Vi sarei grato se inoltraste l’avviso a potenziali interessati.
Un caro saluto,
Giacomo
On behalf of Prof Di Serio I am sharing the following announcement
———————-
The Statistical Network Science committee of the Bernoulli Society invites you to an online talk this week Thursday:
Thursday May 16
2-3 pm UK time
Title: Bayesian network structural learning from complex survey data
Statistical Network Science Seminar Series- Bernoulli Society
Speaker: Paola Vicard (Department of Economics, Università Roma Tre, Rome, Italy)
Abstract: The association structure of a Bayesian network can be known in advance by subject matter knowledge or have to be learned from a database. One of the most widely used procedures is the PC algorithm consisting in carrying out several independence tests on the available data set and in building a Bayesian network according to the tests results. In case of data driven learning, the PC algorithm is based on the irremissible assumption that data are independent and identically distributed. Unfortunately, official statistics data are generally collected through complex sampling designs, then the aforementioned assumption is not met. In such a context the PC algorithm fails in learning the structure. To avoid this, the sample selection must be taken into account in the structural learning process. A modified version of the PC algorithm is proposed for inferring causal structure from complex survey data. It is based on resampling techniques for finite populations. A simulation experiment showing the robustness with respect to departures from the assumptions and the good performance of the proposed algorithm is carried out.
(Joint work with Daniela Marella, Sapienza Università di Roma)
Zoom link
https://eur02.safelinks.protection.outlook.com/?url=https%3A%2F%2Fzoom.us%2…<https://zoom.us/j/99820613967>
Meeting ID: 998 2061 3967
Passcode: 850644
All welcome
Clelia Di Serio and Gesine Reinert