Dear Colleagues,
please find enclosed some information on the Master of Science in Economics of the Department of Economics and Finance of the University of Rome “Tor Vergata”.
Do not hesitate to contact me if you need further information.
Best regards
Paolo Gibilisco
Associate Professor
Department of Economics and Finance
University of Rome “Tor Vergata”
Via Columbia 2, Rome, 00133, Italy
Phone: +39-06-72595956
Email: paolo.gibilisco(a)uniroma2.it <mailto:paolo.gibilisco@uniroma2.it>
Home page: https://economia.uniroma2.it/def/faculty/142/gibilisco-paolo <https://economia.uniroma2.it/def/faculty/142/gibilisco-paolo#>
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Dear Colleague,
I am pleased to announce the 2020/2021 edition of the Master of Science in Economics <https://economia.uniroma2.it/master-science/economics> at the Department of Economics and Finance of Tor Vergata University of Rome. I would be grateful if you could help me spread the information about our program and recommend us to your most talented and motivated students.
The MSc Economics (LM-56) is a two-year graduate program entirely taught in English and designed for highly qualified students. It provides students with a thorough knowledge and understanding of the concepts, tools and methods of economics, together with the application of these methods to the analysis of economic problems.
We are committed to providing our students with high quality teaching from some of the best in the Department, which was recognized as a department of excellence by the MIUR. We have already prepared contingency plans, including options for studying remotely, in the event that our standard practices must be changed due to the COVID-19 epidemic. An important characteristic of the program is that we follow our students closely. They are provided with academic support and a personal tutor who follows them throughout the entire program. Moreover, annual extra-curricular initiatives are organized to strengthen their professional skills and to allow easy access to employment or further academic opportunities.
We offer study grants for the best students enrolling in the first year as well as monetary awards to the best-performing first-year students. Selected second-year students have the opportunity to attend a Dual Degree Program in partnership with the University of Gothenburg or the University of Konstanz. Additional funding is also awarded to students to encourage participation in Summer Schools, database purchases, GRE test and MATLAB Associate Level Certification.
The MSc Economics is the ideal program for those who want to acquire advanced analytical skills to pursue a career in national and international institutions, or who want to prepare for a Ph.D. program in Economics. The excellent placement of our graduates may be consulted on the employment statistics page <https://economia.uniroma2.it/master-science/economics/employment-statistics…> and on the Alumni page <https://economia.uniroma2.it/master-science/economics/Alu/> of our website.
Applications are currently open for the 2020/2021 academic year. The application deadline is June 30, 2020 for non-EU students and August 16, 2020 for EU students. The Call for applications is available here <https://economia.uniroma2.it/master-science/economics/admissions/>, feel free to share this link with interested candidates and other colleagues from your institution.
I will be available to provide additional information during the Online Open Day on June 16, 2020 <https://economia.uniroma2.it/cal/855/msc-economics-online-open-day#.XsVCUC-…> at 5pm on Microsoft Teams.
Should you wish to have additional information or discuss anything related to the program, please do not hesitate to contact me.
Best regards,
Alberto Iozzi
Master of Science in Economics, Director
-----------------------------------------------------------------
Prof. Alberto Iozzi
Department of Economics and Finance
Tor Vergata University of Rome
Via Columbia 2, 00133 Rome - Italy
Tel. +39 06 7259 5923
Fax + 39 06 2040 219
Webpage: sites.google.com/view/albertoiozzi/home <https://sites.google.com/view/albertoiozzi/home>
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WEBINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO
<https://www.carloalberto.org/research/webinars/>
Venerdì 29 Maggio 2020, alle ore 15:00, si terrà il seguente webinar:
------------------------------------------------
Tommaso RIGON (Duke University)
*A generalized Bayes framework for probabilistic clustering*
Abstract:
Clustering methods such as k-means and its variants are standard tools for
finding groups in the data. However, despite their huge popularity, the
underlying uncertainty can not be easily quantified. On the other hand,
mixture models represent a well-established inferential tool for
probabilistic clustering, but they are characterized by severe
computational bottlenecks and may have unreliable solutions in presence of
misspecifications. Instead, we rely on a generalized Bayes framework for
probabilistic clustering based on Gibbs posteriors. Broadly speaking, in
such a setting the log-likelihood is replaced by an arbitrary loss function
and this arguably leads to much richer families of clustering methods. Our
contribution is two-fold: first, we describe a clustering pipeline for
efficiently finding groups and then quantifying the associated uncertainty.
Second, we discuss two broad classes of loss functions which have
advantages in terms of analytic tractability and interpretability.
Specifically, we consider losses based on Bregman divergences and pairwise
dissimilarities and we show they can be interpreted as profile and
composite log-likelihoods, respectively. Full Bayesian inference is
conducted via Gibbs sampling but efficient deterministic algorithms are
available for point estimation. As an important byproduct of our work, we
show that several existing clustering approaches can be interpreted as
generalized Bayesian estimators under specific loss functions. Hence, our
methodology can be also used to formally quantify the uncertainty in widely
used clustering approaches.
(joint work with Amy Herring and David Dunson, Duke University)
------------------------------------------------
Chiunque volesse collegarsi al webinar è pregato di inviare una email entro
mercoledi 27 Maggio a
pierpaolo.deblasi(a)unito.it
Il webinar è organizzato dalla "de Castro" Statistics Initiative
www.carloalberto.org/stats
in collaborazione con il Collegio Carlo Alberto.
Cordiali saluti,
Pierpaolo De Blasi
---
University of Torino & Collegio Carlo Alberto
carloalberto.org/pdeblasi
<https://sites.google.com/a/carloalberto.org/pdeblasi/>
Car* collegh*,
vi segnalo questo evento on-line:
LMS Invited Lecture Series 2020
Fractional Calculus and Fractional Stochastic Calculus, Including
Rough-Paths, with Applications, 15 Jun, 09:00 – 19 Jun, 16:00
https://www.lms2020.boguslavsky.net/
con lezioni di Yulia Mishura, Taras Shevchenko National University of Kyiv,
Ukraine e vari seminari su temi correlati.
Dalla pagina web e' possibile registrarsi.
Cordiali saluti,
Enrico Scalas
Dear Colleagues,
I would like to bring to your attention a postdoc opening (University
Assistant) in Vienna, details are below.
Kind regards
Ulisse Stefanelli
************************************************
The Faculty of Mathematics of the University of Vienna is inviting
applications for a University-Assistant position (postdoc), limited to 3
years. We are looking for a highly qualified researcher with strong
background in calculus of variations or evolution equations, also of
stochastic type.
The start date is 1.7.2020 or as soon as possible thereafter. The position
comes with max. 4h of teaching per week, mostly exercise classes. The
monthly gross salary is in the range 3.8-4.3 K€, depending on the
experience level.
Applications have to be submitted via the jobcenter of the University of
Vienna:
https://personalwesen.univie.ac.at/jobs-recruiting/job-center/
by navigating to 'Aktuelle Stellenausschreibungen', reference number 10846.
Informal enquiries to ulisse.stefanelli(a)univie.ac.at
________________________________________
Ulisse Stefanelli (Univ.-Prof., PhD)
Faculty of Mathematics, University of Vienna
Oskar-Morgenstern-Platz 1,1090 Vienna, Austria
ulisse.stefanelli(a)univie.ac.at
________________________________________
Carissimi
nei pomeriggi dei giorni 1-2 e 8-9 Luglio si terrà in modalità online
un workshop dal titolo:
"Kick-Off Meeting of Prin 2017 Project: Stochastic Models for Complex Systems"
(PRIN articolato nelle sedi di Lecce, Salerno e Napoli)
dedicato alla presentazione dei primi risultati scientifici ottenuti
nell'ambito del progetto. Per tutti i dettagli vi invitiamo a
collegarvi al sito dedicato seguendo il link qui sotto:
https://sites.google.com/view/kick-off-meeting/home
Cari saluti
Roberta Schiattarella, Mariella Longobardi, Nello Buonocore,
Igia Caputo, Enrica Pirozzi.
--
Enrica Pirozzi
Dipartimento di Matematica e Applicazioni
Universita' di Napoli FEDERICO II
Via Cintia, Monte S.Angelo, 80126, NAPOLI, ITALY
Tel. 081 675634
https://www.docenti.unina.it/ENRICA.PIROZZI
Caro Collega,
la Scuola IMT Lucca (www.imtlucca.it) sta valutando l'opportunità di
bandire a breve una posizione di ricercatore a tempo determinato di tipo B
nell'area del Machine Learning. Dato che il tema è affrontato da varie
comunità scientifiche, il settore scientifico disciplinare nel quale
bandire verrà scelto a valle della raccolta di espressioni di interesse.
Chiunque fosse interessato alla posizione di cui sopra è pregato di inviare
al decano, Prof. Rocco De Nicola (rocco.denicola(a)imtlucca.it) un cv e un
breve *statement* motivazionale, *preferibilmente entro il 15 giugno 2020.*
Di seguito riporto il profilo che è stato recentemente deliberato dagli
organi della Scuola. Pregherei di inoltrare questo messaggio a chiunque
fosse a conoscenza di potenziali interessati.
Rimango a disposizione per qualsiasi altro dettaglio.
Cari saluti,
Irene Crimaldi
--------PROFILO:
L'assunzione di un esperto di Machine Learning è finalizzata ad accrescere
le competenze sui metodi quantitativi per lo sviluppo di modelli di sistemi
dinamici e alla loro previsione, regolazione e ottimizzazione, della Scuola
IMT. Questa figura da un lato alimenterà l’arsenale di competenze
metodologiche della Scuola e dall'altro lato sarà funzionale a fornire
strumenti quantitativi alle aree dell'economia e del management nonché
dell'analisi e gestione del patrimonio, delle attività e dei fenomeni
culturali. Il ricercatore, oltre a consolidate conoscenze ed ottime
pubblicazioni nel settore del machine learning, con particolare riferimento
alle tematiche dell’apprendimento basato su reti neurali e alberi
decisionali, dell’identificazione di sistemi dinamici, degli algoritmi di
ottimizzazione, della regressione e all’analisi statistica multivariata,
dovrà dimostrare la capacità di applicare le proprie competenze a problemi
reali e di collaborare in attività di ricerca di tipo multidisciplinare.
Prego di dare la massima diffusione presso i potenziali interessati
ITA
E' uscito il bando di ammissione al 36esimo ciclo di dottorato presso il Politecnico di Milano,
con scadenza il ** 29 Maggio, ore 14 **
http://www.dottorato.polimi.it/fileadmin/files/dottorato/concorso_linkweb/B…
Sono disponibili varie borse in area Statistica / Data Science.
Nell'ambito del dottorato in Metodi e Modelli Matematici per l'Ingegneria sono disponibili 8 borse libere, per le quali i candidati possono proporre progetti in area Statistica / Data Science
Contatti: alessandra.guglielmi(a)polimi.it, anna.paganoni(a)polimi.it, laura.sangalli(a)polimi.it
Nell'ambito del dottorato in Data Analytics and Decision Sciences sono disponibili le borse
- "Patient representation methods for risk stratification in oncology"
Contatto: francesca.ieva(a)polimi.it
- "Impact Analysis in Real World Clinical Oncology"
Contatto: anna.paganoni(a)polimi.it
- "Learning analytics to support policies and managerial decision making in educational institutions"
Contatto: anna.paganoni(a)polimi.it
- “Cyber-Capital and impact on the urban rent”
Contatti: valeria.fedeli(a)polimi.it, simone.vantini(a)polimi.it
- "Neurosciences and genomics: advanced data analytic methods"
Contatto: laura.sangalli(a)polimi.it
ENGLISH:
Several fellowships are available for a PhD in the area of Statistics / Data Science at Politecnico di Milano, Italy:
Call: http://www.dottorato.polimi.it/en/
Deadline for applications: 29 May 2020 at 14:00, Italian time
Within the PhD program in Mathematical Models and Methods in Engineering 8 fellowships are available in the generic field of Mathematics and Statistics, that can be targeted to Statistics / Data Science
Contacts: alessandra.guglielmi(a)polimi.it, anna.paganoni(a)polimi.it, laura.sangalli(a)polimi.it
Within the PhD program in Data Analytics and Decision Sciences fellowships on the following topics are available:
- "Patient representation methods for risk stratification in oncology"
Contact: francesca.ieva(a)polimi.it
- "Impact Analysis in Real World Clinical Oncology"
Contact: anna.paganoni(a)polimi.it
- "Learning analytics to support policies and managerial decision making in educational institutions"
Contact: anna.paganoni(a)polimi.it
- “Cyber-Capital and impact on the urban rent”
Contacts: valeria.fedeli(a)polimi.it, simone.vantini(a)polimi.it
- "Neurosciences and genomics: advanced data analytic methods"
Contact: laura.sangalli(a)polimi.it
——
Laura Maria Sangalli
MOX - Dipartimento di Matematica
Politecnico di Milano
Piazza Leonardo da Vinci 32
20133 Milano - Italy
tel: +39 02 2399 4554
fax: +39 02 2399 4568
email: laura.sangalli(a)polimi.it
url: http://mox.polimi.it/~sangalli
*2020/21 PhD Programs at the IMT School for Advanced Studies Lucca*
Deadline for applications – July 10th 2020, 12 pm CEST
Applications are now being accepted for the 2020/21 PhD Programs at the IMT
School for Advanced Studies Lucca (www.imtlucca.it), one of the six Schools
of Excellence in Italy and one of the highest rated graduate schools in
Europe according to the most recent U-Multirank survey. Highly motivated
candidates from all disciplines are invited to apply for one of the *32
fully-funded positions.* The 32 scholarships are equally divided between
the two doctoral Programs that integrate scientific competences of
economics, engineering, computer science, neuroscience and behavioral
psychology, physics, applied mathematics, statistics, history and sciences
of cultural heritage.
*Economics, Networks and Business Analytics* is one of the four
field-specific tracks offered and is under the “Systems Science” PhD
Program. This Track provides participants with a solid knowledge on modern
analytical methods in economics and management. With its multidisciplinary
approach, the track is unique in its deployment of a strong integration of
concepts, analytical foundations, and practical expertise, to educate the
new generation
of economists, scientists and practitioners with distinctive capabilities
in analyzing, interpreting, and managing complex socio-economic systems.
Graduates will be trained to become researchers and decision makers in
academia, policy and industry by integrating knowledge at the boundary of
Economics, Statistical Physics, Computer and Social Sciences with the
unifying language of Mathematics and Statistics. Close associations with a
selected set of companies and institutions provide the opportunity to
analyze relevant problems, motivating new
analytical techniques from practical problem solving. Students are involved
in the analysis of real world high dimensional data, in collaboration with
companies and institutions. During their doctoral studies, students are
encouraged to carry out their research with the School’s Research Units.
ENBA students also have the possibility of completing their theses under
the joint supervision (Double-degree) with KU Leuven or the University of
Alicante.
Courses are led by world-renowned researchers and provide students with all
the theoretical skills and advanced tools required for rigorously tackling
a multitude of analysis, design and management problems within the broad
framework of systems analysis in economic, social, scientific,
technological and cultural domains. Specialized faculty and staff create a
network that provides key guidance and support throughout the PhD Program.
Working closely with faculty, both in the classroom and in the development
of research, students reach the highest levels of
scholarly achievement. IMT School PhD graduates will be able to use the
skills they acquired during their studies to recognize and resolve complex
problems, to choose the most appropriate method or instrument to utilize
when approaching these problems, even in disciplines outside of their
primary field of research.
All students are based in the recently restored San Francesco complex, *a
fully integrated Campus* in the historical center of the beautiful Tuscan
city of Lucca. The Campus includes renewed residential facilities, an
on-site canteen, study and living rooms, a state-of-the-art library and
outdoor recreational spaces, which foster a unique cultural,professional
and social environment for our doctoral program. Eligible students, in
addition to
*free room and*
*board,* will also receive a *research scholarship which amounts to
approximately €15,300/year. *The scholarships are *fully-funded for up to
four years,* with a possibility of graduating after the third year.
The PhD Programs at the IMT School attracts students from around the world,
providing a truly international environment. English is the official
language of the School. Moreover, all students will have the opportunity to
spend periods abroad at research institutes, laboratories or universities,
both within the Erasmus+ framework and through ad hoc mobility agreements.
Most IMT School PhD Graduates have reached prominent roles in academics,
governmental institutions, public and private companies or professions
across the globe.
To find out more about the School, the admission requirements and how to
apply, please visit the following link:
https://www.imtlucca.it/en/phd/information-for-students
*Deadline for applications – July 10th 2020, 12 pm CEST*
Find the IMT School on Facebook, Twitter, LinkedIn and YouTube for the
latest news.
*Advertiser: Department of Economics, Ca' Foscari University Venice
(Università Ca’ Foscari)**
**Field(s) of specialization: Econometrics*
Position type(s): Research Assistant
Target date for applications: 25 May 2020
Application deadline: 31 May 2020 (accepting applications)
CALL OF INTEREST
POSITIONS AS RESEARCH FELLOW AT ITALIAN UNIVERSITIES:
University of Bologna, *Ca' Foscari University*, Free University of
Bozen-Bolzano
Under the Italian PRIN Project entitled “Hi-di network econometric
analysis of high dimensional models with network structures in
macroeconomics and finance – PROT. 2017TA7TYC” funded by the Italian
Ministry of Education, the Departments of Economics at the University of
Bologna, the *Department of Economics of the Ca’ Foscari University of
Venice* and the Faculty of Economics and Management at Free University
of Bozen-Bolzano are opening a call of interest for three positions as
Research Fellow (one position for each university). The positions will
be funded by the project up to 24 months.
The research project covers the following topics:
*(i) Development of novel multivariate econometric models and methods
able to deal with network effects and to take into account time varying
relationships. Attention will be paid on how latent factors drive
economic systems and are subject to instability. Their roles will be
studied and compared in the pre- and post-coronavirus era.**
*
*(ii) Analysis of interconnected networks: either physical or intangible
networks, observed or estimated. Results will expand academic knowledge
on statistical modelling of network event data in a broad range of areas
including, but not limited to, social media information diffusion,
economic/financial crises contagion and epidemic/disease spread
phaenomena.**
*
(iii) Economic impact of uncertainty: uncertainty is expected to act as
a key driving factor in the aftermath of the covid-19 shock and the
focus will be also on the policy actions necessary at the macro level to
offset the economic consequences of a shock of size never experienced by
world economies after WW2.
Interested researchers can express their willingness to apply not later
than 31st May 2020. Applications should include the CV of the candidate
a short research proposal related to the topics covered by the project,
and the indication of the University where the research activity will be
carried out.
For further information please contact:
*- Monica Billio (billio(a)unive.it) - Department of Economics of the Ca’
Foscari University of Venice**
*
- Giuseppe Cavaliere (giuseppe.cavaliere(a)unibo.it) - Departments of
Economics at the University of Bologna
- Francesco Ravazzolo (francescoravazzolo(a)unibz.it) - Faculty of
Economics and Management at Free University of Bozen-Bolzano
--
Roberto Casarin, PhD
Professor of Econometrics
University Ca' Foscari, Venice
Address: San Giobbe 873/b
30121 Venezia, Italy
Phone: +39 041.234.91.49
Web: http://sites.google.com/view/robertocasarin/
IMEF: http://www.unive.it/imef
VERA: http://www.unive.it/vera
ORCID: https://orcid.org/0000-0003-1746-9190
--
Questa e-mail è stata controllata per individuare virus con Avast antivirus.
https://www.avast.com/antivirus
WEBINARS IN STATISTICS @ COLLEGIO CARLO ALBERTO
<https://www.carloalberto.org/research/webinars/>
Venerdì 22 Maggio 2020, alle ore 12:00, si terrà il seguente webinar:
------------------------------------------------
Pierre JACOB (Harvard University)
*Unbiased Markov chain Monte Carlo with couplings*
Abstract:
Various tasks in statistics involve numerical integration, for which Markov
chain Monte Carlo (MCMC) methods are state-of-the-art. MCMC methods yield
estimators that converge to integrals of interest in the limit of the
number of iterations. This iterative asymptotic justification is not ideal;
first, it stands at odds with current trends in computing hardware, with
increasingly parallel architectures; secondly, the choice of "burn-in" or
"warm-up" is arduous. This talk will describe recently proposed estimators
that are unbiased for the expectations of interest while having a finite
computing cost and a finite variance. They can thus be generated
independently in parallel and averaged over. The method also provides
practical upper bounds on the distance (e.g. total variation) between the
marginal distribution of the chain at a finite step and its invariant
distribution. The key idea is to generate "faithful" couplings of Markov
chains, whereby pairs of chains coalesce after a random number of
iterations. This talk will provide an overview of this line of research.
(joint work with John O'Leary, Yves Atchadé)
Paper at:
https://rss.onlinelibrary.wiley.com/doi/abs/10.1111/rssb.12336
------------------------------------------------
Chiunque volesse collegarsi al webinar è pregato di inviare una email entro
mercoledi 20 Maggio a
pierpaolo.deblasi(a)unito.it
Il webinar è organizzato dalla "de Castro" Statistics Initiative
www.carloalberto.org/stats
in collaborazione con il Collegio Carlo Alberto.
Cordiali saluti,
Pierpaolo De Blasi
---
University of Torino & Collegio Carlo Alberto
carloalberto.org/pdeblasi
<https://sites.google.com/a/carloalberto.org/pdeblasi/>