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PhD in Statistics -- Bocconi University, Milano
Call for applications for PhD student positions
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The PhD School of Bocconi University, Milano, offers four positions with
scholarships for the PhD in Statistics.
The scholarship amounts to 20.280 euro per annum in the 1st and 2nd
year, and 13.838 euro per annum for the 3rd and 4th year. Further
funding is available for teaching and research assistanships.
Visit www.unibocconi.eu/admissionphd for all information.
** Applications are due by February 1, 2018. **
Within the PhD School at Bocconi University, the four-year PhD program
in Statistics provides a solid grounding for high level research, either
theoretical or applied, in statistics, probability and data science.
The curricula is organized over two years of courses and two years
entirely devoted to research. Students acquire a deep mathematical and
methodological preparation through the first-year courses, and more
specialized competence, addressed to the doctoral dissertation, through
the second-year courses. The third and forth years are entirely devoted
to research. Both theoretical and applied research, including methods
for machine learning and data science, are supported and encouraged.
Multidisciplinary interchange with other graduate programs in Bocconi’s
PhD School, as well as research experience abroad, are also encouraged.
The PhD in Statistics is designed for highly motivated students who wish
to undertake first-rate research careers in theoretical or applied
statistics and data science. Career opportunities also include central
banks, financial institutions, governments and international
organizations, and public health institutions.
Highly qualified and motivated students with M.Sc. degrees in
Statistics, Mathematics, Economics, Engineering, 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 more information about the PhD program in Statistics at Bocconi,
visit our website www.unibocconi.eu/phdstatistics and please feel free
to contact the PhD Director, Professor Sonia Petrone, at
sonia.petrone(a)unibocconi.it or our Program Assistant at
infophd(a)unibocconi.it
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PhD School - Università Bocconi
Via Roentgen, 1
20136 Milano (Italia)
Tel.+39-02.5836.3367 angela.baldassarre(a)unibocconi.it
The position will be held in the probability group at the University of
Bath, under the supervision of Alexandre Stauffer. The project is flexible,
but the main areas of interest are interacting particle systems, random
walks, and Markov chain mixing time.
Applications should be submitted through the online system (see
http://www.bath.ac.uk/math-sci/postgraduate/).
Interested candidates are encouraged to write to a.stauffer(a)bath.ac.uk to
discuss their research interests.
Best wishes,
Alexandre
Giovedi' 18 Gennaio, ore 12.00, Aula C
Speaker: M. Maurelli (WIAS, Berlin)
Title: Enhanced Sanov theorem for Brownian rough paths and an application
to interacting particles
Abstract: We establish a Sanov type large deviation principle for an
ensemble of interacting Brownian rough paths. As application a large
deviations principle for the (k-layer, enhanced) empirical measure of
weakly interacting diffusions is obtained. This in turn implies a
propagation of chaos result in rough path spaces and allows for a robust
subsequent analysis of the particle system and its McKean-Vlasov type
limit. The talk is based on a work in collaboration with J.D. Deuschel, P.
Friz and M. Slowik
--
*************************************************
Prof. Alessandra Faggionato
http://www1.mat.uniroma1.it/~faggionato/
Department of Mathematics
University "La Sapienza"
Piazzale Aldo Moro, 5
00185 - Rome
Office 5, Phone (0039) 06 49913252
*************************************************
STATISTICS SEMINARS @ COLLEGIO CARLO ALBERTO
Venerdì 19 Gennaio 2018, alle ore 12:00, presso il nuovo edificio del Collegio Carlo Alberto, in Piazza Arbarello 8, Torino, si terra' il seguente seminario:
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Davide LA VECCHIA (University of Geneva)
SADDLEPOINT TECHNIQUES FOR DEPENDENT DATA
Saddlepoint techniques provide numerically accurate, higher-order, small sample approximations to the distribution of estimators and test statistics. While a rich theory is available for saddlepoint techniques in the case of independently and identically distributed observations, only a few results have been obtained for dependent data. In this talk, we explain how to fill this gap in the literature. Using the method of the tilted-Edgeworth expansion, we devise new saddlepoint density approximations and saddlepoint test statistics in the settings of time series (short or long memory) and spatial processes (panel data models, with fixed effects, time-varying covariates and spatially correlated errors). We compare our new approximations to the ones obtained by standard asymptotic theory, by Edgeworth expansion and by resampling methods. The numerical exercises illustrate that our approximations yield accuracy's improvements, while preserving analytical tractability.
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Tutti gli interessati sono invitati a partecipare.
Il seminario e' organizzato dalla "de Castro" Statistics Initiative (www.carloalberto.org/stats <http://www.carloalberto.org/stats>) in collaborazione con il Collegio Carlo Alberto.
Cordiali saluti,
Matteo Ruggiero
---
Matteo Ruggiero
University of Torino and Collegio Carlo Alberto
www.matteoruggiero.it
Dear Colleagues,
on 24 January 2018 from 9:30 to 13:00 (Aula 8, Department of Business
Studies-Roma Tre University, Via Silvio D'Amico, 77 -00145, Roma ), Dr.
Angela Loregian, senior researcher at ARPM, will hold a min-workshop on
"Advanced statistical techniques across disparate asset classes".
The attendance of the course is free, but for organizational reasons it is
necessary to register by sending an email to francesco.cesarone(a)uniroma3.it
with the following subjects:
Name Surname - ARPM min-workshop.
*About the Program.* *We introduce the concept of "risk driver" and
**"invariant“,
illustrating:*
*- the asset-specific art of building risk drivers across the financial
markets*
*- the asset-agnostic science of applying statistics (econometrics and
**machine
learning) to extract the invariants and estimate their joint *
*distribution. **Then, we translate the above statistical analysis into the
asset-specific **joint distribution of instrument returns.*
For more details, see the attached pdf file.
We look forward to meeting you in Roma Tre!
Best regards,
Francesco Cesarone
--
http://disa.uniroma3.it/qfw2018/
--
Francesco Cesarone - Ph.D.
Ricercatore - Assistant Professor
Facoltà di Economia
Dipartimento di Studi Aziendali
Università Roma Tre
Via Silvio D'Amico, 77
00145 - Roma
tel: +39 06 57335744
Skype: francesco.cesarone
email: francesco.cesarone(a)uniroma3.it
Studio n. 20 piano V
WWW: http://host.uniroma3.it/docenti/cesarone/
Dear Colleagues,
on 23 January 2018 from 14:00 to 17:00 (Computer Lab, ground floor,
Department of Business Studies-Roma Tre University, Via Silvio D'Amico, 77
-00145, Roma), Dr. Francesca Perino, Application Engineer at MathWorks,
will hold a min-workshop on "Machine Learning and Big Data Analytics with
MATLAB".
The attendance of the course is free, but for organizational reasons it is
necessary to register to register on the following web page:
https://it.mathworks.com/company/events/seminars/ml-da-with-matlab-2373496.…
.
*Overview*
*At the heart of many financial applications are machine learning
techniques used for risk classification, economic analysis, credit scoring,
time series forecasting, estimating default probabilities, and data
mining. Big data represents an opportunity for quantitative analysts and
data scientists alike to impact the way organizations make informed
business decisions. By building machine learning models that harness big
data, a greater level of insight and confidence can be achieved.*
*However, implementing and comparing machine learning techniques to choose
the best method can be challenging. Furthermore, there is no single
approach to solving the many challenges arising from working with big
data. MATLAB minimizes these challenges by providing you with a number of
built-in functions and tools for quick prototyping, integration, and
scaling, to take you from initial prototype all the way to
business-critical production system.*
*In this session, we will introduce ways of working with big data systems,
the different types of machine learning techniques in MATLAB, how to
determine the best techniques for your problem by evaluating model
performance, and rapidly deploying your machine learning models into
production. We will cover several new workflows and data types in MATLAB
and the toolboxes that have been designed to address the most common
challenges with big data analytics and machine learning.*
*Highlights*
*Data management and integration with databases, live market data, and big
data environments*
*Efficient workflows for heterogenous time-series data using new data
management capabilities*
*Parallel Computing techniques to speed up long-running computations and
deal with out-of-memory data*
*Predictive modeling and using supervised machine learning techniques to
build a credit rating engine*
We look forward to meeting you in Roma Tre!
Best regards,
Francesco Cesarone
--
http://disa.uniroma3.it/qfw2018/
--
Francesco Cesarone - Ph.D.
Ricercatore - Assistant Professor
Facoltà di Economia
Dipartimento di Studi Aziendali
Università Roma Tre
Via Silvio D'Amico, 77
00145 - Roma
tel: +39 06 57335744
Skype: francesco.cesarone
email: francesco.cesarone(a)uniroma3.it
Studio n. 20 piano V
WWW: http://host.uniroma3.it/docenti/cesarone/
Avviso Ciclo di Seminari
Il prof. James O. Berger, Duke University,
https://en.wikipedia.org/wiki/Jim_Berger_(statistician)
sarà ospite del Dipartimento MEMOTEF, Sapienza Università di Roma dal 22 al
26 gennaio 2018.
Nel corso della settimana il prof. Berger terrà una serie di seminari su
Bayesian Model Selection
I seminari si terranno in Aula 6B, al piano terrà della facoltà di
Economia, Via del Castro Laurenziano, 9, secondo il seguente orario:
Lunedì 22 gennaio ore 11-13
Martedì 23 gennaio ore 16.30-18
Mercoledì 24 gennaio 11.30-13
Mercoledì 24 gennaio 14.30-16
I seminari sono rivolti ad un pubblico di dottorandi ma tutti gli
interessati sono invitati a partecipare.
Brunero Liseo
--
============================================
Brunero Liseo
*Dip. di metodi e modelli per il territorio, l'economia e la finanza *
*Sapienza Università di Roma*
*Viale Castro Laurenziano, 9 Roma I-00161 *Tel. +39 06 49766973
Fax +39 06 4957606
*https://sites.google.com/a/uniroma1.it/bruneroliseo/
<https://sites.google.com/a/uniroma1.it/bruneroliseo/>*
============================================
My pevious mail contained a missprint in the title of the school
following is the correct announcement
Gianmario Tessitore
========================================
Dear Colleagues,
This is the first announcement of the upcoming sixth RISM school
DEVELOPMENTS IN STOCHASTIC PARTIAL DIFFERENTIAL EQUATIONS
in honor of Giuseppe Da Prato.
It will take place in Varese during the week July 23-27, 2018 at the
Riemann International School of Mathematics, Universita’ degli Studi
dell'Insubria, and it will be directed by Martin Hairer.
Please find the poster and further details at the link www.rism.it.
The school will consist of three courses delivered by:
Arnaud Debussche (Ecole Normale Superieure Rennes)
Martin Hairer (Imperial College, London)
Felix Otto (Max Planck Institute, Leipzig)
and of three specialized talks aimed at presenting recent advances and
challenges of contemporary research in SPDEs in connection with the work of
Giuseppe Da Prato.
Moreover young participants will be offered the possibility to present
short communications on their own research.
Interested people can register at the link
http://www.rism.it/registration_rism5_45.html
(a modest registration fee will cover 5 lunches and local transportations).
IMPORTANT: PhD students, young researchers and postdocs are invited to
apply for financial support towards lodging expenses by sending a CV to
presidente(a)rism.it
For organizing purposes we kindly ask participants to get registered as
soon as possibe and, in any case, by the end of March 2018.
With very best regards and wishes for a prosperous 2018,
Scientific Committee: M. Hairer (Imperial College - London), S. Cerrai
(University of Maryland), A. Debussche (ENS - Rennes), L. Zambotti
(Universite Pierre et Marie Curie - Paris).
Organizing Committee: D. Cassani (Univ. Insubria), M. Fuhrman (Univ.
Milano), G. Guatteri (Politecnico di Milano), F. Masiero and G. Tessitore
(Univ. Milano-Bicocca)
--
Gianmario Tessitore
Dipartimento di Matematica e Applicazioni
Università degli Studi di Milano-Bicocca
Dear Colleagues,
This is the first announcement of the upcoming sixth RISM school
DEVELOPMENTS IN STOCHASTIC DIFFERENTIAL EQUATIONS
in honor of Giuseppe Da Prato.
It will take place in Varese during the week July 23-27, 2018 at the
Riemann International School of Mathematics, Universita’ degli Studi
dell'Insubria, and it will be directed by Martin Hairer.
Please find the poster and further details at the link: www.rism.it.
The school will consist of three courses delivered by:
Arnaud Debussche (Ecole Normale Superieure Rennes)
Martin Hairer (Imperial College, London)
Felix Otto (Max Planck Institute, Leipzig)
and of three specialized talks aimed at presenting recent advances and
challenges of contemporary research in SPDEs in connection with the work of
Giuseppe Da Prato.
Moreover young participants will be offered the possibility to present
short communications on their own research.
Interested people can register at the link
http://www.rism.it/registration_rism5_45.html
(a modest registration fee will cover 5 lunches and local transportations).
IMPORTANT: PhD students, young researchers and postdocs are invited to
apply for financial support towards lodging expenses by sending a CV to
presidente(a)rism.it
For organizing purposes we kindly ask participants to get registered as
soon as possibe and, in any case, by the end of March 2018.
With very best regards and wishes for a prosperous 2018,
Scientific Committee: M. Hairer (Imperial College - London), S. Cerrai
(University of Maryland), A. Debussche (ENS - Rennes), L. Zambotti
(Universite Pierre et Marie Curie - Paris).
Organizing Committee: D. Cassani (Univ. Insubria), M. Fuhrman (Univ.
Milano), G. Guatteri (Politecnico di Milano), F. Masiero and G. Tessitore
(Univ. Milano-Bicocca)
--
Gianmario Tessitore
Dipartimento di Matematica e Applicazioni
Università degli Studi di Milano-Bicocca
Ricevo e inoltro
----------------------------------------
Fabrizio Lillo
Dipartimento di Matematica
Università di Bologna
ITALY
Personal website: fabriziolillo.wordpress.com
University website: www.unibo.it/sitoweb/fabrizio.lillo
<http://fabriziolillo.wordpress.com/>
phone: +39 050509159 <+39%20050%20509159>
---------- Forwarded message ----------
From: Doyne Farmer <Doyne.Farmer(a)inet.ox.ac.uk>
Date: 2017-12-22 13:34 GMT+01:00
Subject: 3 year postdoc at Oxford in economic complex systems modeling
To: Fabrizio Lillo <fabrizio.lillo(a)sns.it>
We are seeking to appoint a Senior Research Associate to participate in the
‘Sensitive Intervention Points in the Transition to the Post-Carbon
Society” project funded by the Oxford Martin School under the leadership of
the Principal Investigators, Professor Doyne Farmer and Professor Cameron
Hepburn. The project will study the transition to carbon neutral energy
generation from economic, sociological and technological points of view.
Key duties include playing a leadership role in managing the project,
working closely with the principal investigators and the other members of
the team to achieve the goals of the project; managing and undertaking
academic research and write articles for publication in scientific
journals; managing and co-ordinating research activities, administrative
activities and grant reporting; playing a mentoring role, and act as a
source of information and advice to other members of the group;
disseminating research and presenting research outputs at conferences,
workshops and to stakeholders; and developing ideas for generating research
income and take a leadership role in finding additional sources of funding
and making applications for research grants.
The successful candidate will have ability to undertake interdisciplinary
research, with strong skills in mathematics, programming, and large-scale
data analysis; a PhD/DPhil in a field of quantitative science such as
economics, mathematics, physics, computer science, social science, biology,
statistics or engineering; fluency in written and spoken English; and a
demonstrated track record in writing papers for publication. An ability to
work in a demanding environment subject to deadlines and exacting
professional and academic standards is essential.
The appointment will be available for up to 36 months.