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Research Fellow and PhD in Ethical Machine Learning at University of Sussex, UK
by Enrico Scalas 19 Jul '17

19 Jul '17

Car* Collegh*, vi invio due bandi con preghiera di diffusione a persone interessate. Cordiali saluti, Enrico Scalas *** *Research Fellow in Ethical Machine Learning at University of Sussex, UK* *** A research position funded by the EPSRC is available in the group of Dr Novi Quadrianto on a project titled “EthicalML: Injecting Ethical and Legal Constraints into Machine Learning Models”. The long-term goal of the project is to develop a probabilistic machine learning framework with plug-and-play constraints that is able to handle fairness, transparency, and confidentiality constraints, their combinations, and also new constraints that might be stipulated in the future. The successful candidate will participate in the research activities in the Predictive Analytics Lab (PAL) co-directed by Dr Quadrianto at Sussex. The successful candidate will engage in a number of exciting ongoing national and international research collaborations of PAL (e.g. with the Leverhulme Centre for the Future of Intelligence, universities in Cambridge, Sydney, Moscow, and Darmstadt) in the topics of privileged learning, Bayesian methods, and deep learning. In addition to undertaking high quality research and publishing in top machine learning conferences/journals including NIPS, ICML, JMLR, and TPAMI, the PAL group also creates significant impact by providing support, technology, and highly-trained specialists to a new generation of technology companies. It is expected that the successful candidate will take a leadership role in supporting the group activities including the supervision of Ph.D and MSc students. The successful candidate will normally be of doctoral level or equivalent qualification. Research experience in machine learning is essential. Experience with Bayesian methods and non-convex optimization is a distinct advantage. For full details and how to apply see: http://www.sussex.ac.uk/about/jobs/research-fellow-ethical-m achine-learning-2313. Applications must be received by midnight of 10th September 2017. Informal enquiries are welcome and can be made to Novi Quadrianto ( http://www.sussex.ac.uk/profiles/335583) *** PhD Studentship in Ethical Machine Learning *** Location: Falmer, Brighton "London-by-Sea", UK Funding amount: £14,553 tax free stipend plus UK/EU tuition fees waiver Start Date: 1st October 2017 A PhD position is available in the Predictive Analytics Lab (PAL) in the Department of Informatics at the University of Sussex. The PhD position is linked with an EPSRC funded project titled "EthicalML: Injecting Ethical and Legal Constraints into Machine Learning Models". The long-term goal of the project is to develop a probabilistic machine learning framework with plug-and-play constraints that is able to handle fairness, transparency, and confidentiality constraints, their combinations, and also new constraints that might be stipulated in the future. The successful candidate will engage in a number of exciting ongoing national and international research collaborations of PAL (e.g. with the Leverhulme Centre for the Future of Intelligence, universities in Cambridge, Sydney, Moscow, and Darmstadt) in the topics of privileged learning, Bayesian methods, and deep learning. In addition to undertaking high quality research and publishing in top machine learning conferences/journals including NIPS, ICML, JMLR, and TPAMI, the PAL group also creates significant impact by providing support, technology, and highly-trained specialists to a new generation of technology companies. University of Sussex is a research intensive university, in the sunniest part of UK, 50min by train to Central London, and 30min by cycle to the Brighton Beach (which has a 300m long zip wire). Requirements · Good Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Physics or related disciplines (essential) · Good programming skills in at least one of Python/R/Matlab/C++ (essential) · Ability to work independently and be self-motivated (essential) · Experience in machine learning (desirable) Timetable The studentship will be allocated as soon as a suitable candidate is found. Review of applications will commence on 10th September 2017 and will continue until the position is filled. Early application is advised. Procedure Applications must be submitted via the University of Sussex Postgraduate Admissions System at https://www.sussex.ac.uk/pgapplication/. Please select Informatics PhD as your programme of study and indicate Dr. Novi Quadrianto as your preferred supervisor. For more information Informal enquiries are welcome and can be made to Novi Quadrianto ( http://www.sussex.ac.uk/profiles/335583)

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Call for interest ricercatore in finanza matematica
by Daniele Marazzina 18 Jul '17

18 Jul '17

Il Dipartimento di Matematica del Politecnico di Milano è alla ricerca di manifestazioni di interesse per una posizione di ricercatore a tempo determinato o a tempo determinato in tenure track (RTDA o RTDB) nel settore scientifico disciplinare SECS-S/06 con un focus nell’ambito della finanza matematica. Gli interessati possono inviare la loro manifestazione di interesse all’indirizzo application-dmat(a)polimi.it<mailto:application-dmat@polimi.it> specificando nell’oggetto del messaggio ‘’finanza matematica’’ ed allegando: -curriculum vitae e lista delle pubblicazioni, -lettera di motivazione/interesse per la posizione e per il Politecnico di Milano, -eventuali lettere di referenze. Per essere prese in considerazioni, le manifestazioni di interesse debbono essere inviate entro il 18 settembre 2017 ore 24.00. Eventuali richieste di informazioni possono essere inviate all’indirizzo di cui sopra. Sito internet gruppo finanza quantitativa: <https://www.mate.polimi.it/qfinlab/index.php?cate=15>https://www.mate.polimi.it/qfinlab/ Disclaimer Questa è soltanto una richiesta di manifestazioni di interesse e non un annuncio di job vacancy o di una futura procedura di valutazione comparativa nel settore SECS-S/06. Il Dipartimento di Matematica si riserva di valutare se promuovere una procedura di valutazione comparativa e per quale posizione eventualmente farlo. &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& The Department of Mathematics, Politecnico di Milano, Italy, is seeking expressions of interest for positions of researcher (either temporary or temporary in tenure track) in financial mathematics. Notice that a solo temporary position lasts three years (renewable for two years) a temporary position (three years), in tenure track allows the candidate to become associate professor after three years provided that the candidate is habilitated at the national level before the end of the contract. Candidates are invited to apply. Successful candidates will be expected to contribute to the activities of the Department, in particular by doing: Research, by contributing/defining research projects, attracting funding, and contributing to dissemination of results through top-level publications. Teaching, by offering courses for approximately 80 (temporary)/120 (temporary in tenure track) hours per year to students at the undergraduate and graduate level. Management, by serving in committees and boards of our University. Salary is conformal to national standards, gross salary for solo temporary position is 37.000 euro, temporary in tenure track is 50.000 euro. Interested candidates are kindly requested to send at application-dmat(a)polimi.it<mailto:application-dmat@polimi.it>, specifying the reference to ‘‘mathematical finance’’ on the object of the message, the following material: - a complete CV and list of publications - a short letter explaining their interest in working in Italy and at the Department of Mathematics, Politecnico di Milano - (eventually) reference letters. Applications to be considered should reach by 18 September 24.00(local time). For requests of information please contact the above email. Quantitative finance group website: https://www.mate.polimi.it/qfinlab/<https://www.mate.polimi.it/qfinlab/index.php?cate=15> Disclaimer Please note that this is a call for interest only, and not a job vacancy advertisement, and that the Department can decide on its own whether or not to open a position and at which level. The actual selection for a position will be based on a public selection procedure pursuant art. 18, comma 1 and 4, of Italian Law 240/2010.

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Fwd: Seminario Elena Di Bernardino a ROMA 1, 20 luglio 2017
by Nappo, Giovanna 17 Jul '17

17 Jul '17

Mi scuso per l'errore del cognome nel precedente messaggio Giovanna Nappo ---------- Forwarded message ---------- From: "Nappo, Giovanna" <nappo(a)mat.uniroma1.it> Date: Mon, 17 Jul 2017 13:38:50 +0200 Subject: Seminario Elena Bernardini a ROMA 1, 20 luglio 2017 To: random <random(a)fields.dm.unipi.it> SEMINARI DI PROBABILITA' E STATISTICA MATEMATICA DIPARTIMENTO DI MATEMATICA Guido Castelnuovo Università di Roma "La Sapienza" Piazzale A. Moro 5 . 00185 ROMA ***************************************************************************** Giovedì 20 luglio 2017, Ore 11,30 Aula di Consiglio Elena Di Bernardino CNAM, Paris (FRANCE) A test of Gaussianity based on the Euler characteristic of excursion sets Abstract: We deal with a stationary isotropic random field X:R^d→R and we assume it is partially observed through some level functionals. We aim at providing a methodology for a test of Gaussianity based on this information. More precisely, the level functionals are given by the Euler characteristic of the excursion sets above a finite number of levels. On the one hand, we study the properties of these level functionals under the hypothesis that the random field X is Gaussian. In particular, we focus on the mapping that associates to any level u the expected Euler characteristic of the excursion set above level u. On the other hand, we study the same level functionals under alternative distributions of X, such as chi-square, harmonic oscillator and shot noise. In order to validate our methodology, a part of the work consists in numerical experimentations. We generate Monte-Carlo samples of Gaussian and non-Gaussian random fields and compare, from a statistical point of view, their level functionals. Goodness-of-fit p−values are displayed for both cases. Simulations are performed in one dimensional case (d=1) and in two dimensional case (d=2), using R. ***************************************************************************************** Tutti gli interessati sono invitati a partecipare Giovanna Nappo

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Seminario Elena Bernardini a ROMA 1, 20 luglio 2017
by Nappo, Giovanna 17 Jul '17

17 Jul '17

SEMINARI DI PROBABILITA' E STATISTICA MATEMATICA DIPARTIMENTO DI MATEMATICA Guido Castelnuovo Università di Roma "La Sapienza" Piazzale A. Moro 5 . 00185 ROMA ***************************************************************************** Giovedì 20 luglio 2017, Ore 11,30 Aula di Consiglio Elena Di Bernardino CNAM, Paris (FRANCE) A test of Gaussianity based on the Euler characteristic of excursion sets Abstract: We deal with a stationary isotropic random field X:R^d→R and we assume it is partially observed through some level functionals. We aim at providing a methodology for a test of Gaussianity based on this information. More precisely, the level functionals are given by the Euler characteristic of the excursion sets above a finite number of levels. On the one hand, we study the properties of these level functionals under the hypothesis that the random field X is Gaussian. In particular, we focus on the mapping that associates to any level u the expected Euler characteristic of the excursion set above level u. On the other hand, we study the same level functionals under alternative distributions of X, such as chi-square, harmonic oscillator and shot noise. In order to validate our methodology, a part of the work consists in numerical experimentations. We generate Monte-Carlo samples of Gaussian and non-Gaussian random fields and compare, from a statistical point of view, their level functionals. Goodness-of-fit p−values are displayed for both cases. Simulations are performed in one dimensional case (d=1) and in two dimensional case (d=2), using R. ***************************************************************************************** Tutti gli interessati sono invitati a partecipare Giovanna Nappo

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Bando RTD-A, SECS-S/06, Università di Firenze
by Giacomo Scandolo 16 Jul '17

16 Jul '17

Il Dipartimento di Scienze per l'Economia e l'Impresa (DISEI), Università degli Studi di Firenze, ha bandito un posto di Ricercatore a Tempo Determinato di tipo A nel SSD SECS-S/06 (Metodi Matematici dell’Economia e delle Scienze Attuariali e Finanziarie). Il bando si trova al link: http://www.unifi.it/cmpro-v-p-11205.html Le domande di partecipazione vanno inviate esclusivamente con la modalità telematica descritta nel bando. Il termine ultimo per l'invio è il 10 agosto 2017. Cordiali saluti Giacomo Scandolo

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Data Science and Statistical Learning Post Doc positions - Human Technopole
by Piercesare Secchi 14 Jul '17

14 Jul '17

The Center for Analysis, Decision and Society of the Human Technopole, based in Milano, Italy (https://htechnopole.it/en/) is opening a few positions for post-doc in data science and statistical learning. Details can be found here: https://htechnopole.it/en/openings ------------------------------------------------ Piercesare Secchi MOX - Dipartimento di Matematica Politecnico di Milano Via Bonardi 9 20133 Milano - Italy tel. +39 02 2399 4592 fax. +39 02 2399 4568 e.mail: piercesare.secchi(a)polimi.it<mailto:piercesare.secchi@polimi.it>

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[Fwd: [gdre-conedp] Post-doctoral position at university Blaise Pascal (France)] (fwd)
by Tiziano Vargiolu 12 Jul '17

12 Jul '17

---------- Forwarded message ---------- Date: Wed, 12 Jul 2017 07:51:42 +0200 From: Fabio Ancona <ancona(a)math.unipd.it> To: users(a)math.unipd.it Subject: [Fwd: [gdre-conedp] Post-doctoral position at university Blaise Pascal (France)]

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2 postdocs in Geometry of Deep Learning and Reinforcement Learning at RIST
by Luigi Malagò 11 Jul '17

11 Jul '17

=========================================================== 2 postdoc positions in Machine Learning (1 year, renewable up to 3 years) Institution: RIST - Romanian Institute of Science and Technology, Cluj-Napoca Keywords: Deep Learning, Reinforcement Learning, Stochastic Optimization, Optimization over Manifolds, Information Geometry, Riemannian Geometry Application deadline: 30 July 2017 (applicants are encouraged to apply earlier) Salary: around 2190 euro net Official announcement: http://rist.ro/en/details/news/postdoc-positions-in-deep-learning-and-machi… =========================================================== Dear colleagues, the Romanian Institute of Science and Technology (RIST) has an opening for 2 postdoc positions, in the context of the DeepRiemann project “Riemannian Optimization Methods for Deep Learning”, funded by European structural funds through the Competitiveness Operational Program (POC 2014-2020). The appointments will be for 1 year, with possible extensions up to 3 years. The DeepRiemann project aims at the design and analysis of novel training algorithms for Neural Networks in Deep Learning, by applying notions of Riemannian optimization and differential geometry. The task of the training a Neural Network is studied by employing tools from Optimization over Manifolds and Information Geometry, by casting the learning process to an optimization problem defined over a statistical manifold, i.e., a set of probability distributions. The project is highly interdisciplinary, with competences spanning from Machine Learning to Optimization, Deep Learning, Statistics, and Differential Geometry. The objectives of the project are multiple and include both theoretical and applied research, together with industrial activities oriented to transfer knowledge, from the institute to a startup or spin-off of the research group. The positions will be part of the new Machine Learning and Optimization group http://luigimalago.it/group.html, which performs research at the intersection of Machine Learning, Stochastic Optimization, Deep Learning, and Optimization over Manifolds, from the unifying perspective of Information Geometry. The group is one of two newly-formed groups in Machine Learning at RIST, where about 20 new postdoctoral research associates and research software developers will be hired by 2018. The official job announcement can be seen here: http://rist.ro/en/details/news/postdoc-positions-in-deep-learning-and-machi… Informal inquiries can be sent to Dr. Luigi Malagò <malago(a)rist.ro>, principal investigator of the DeepRiemann project. Application deadline: 30 July 2017 (applicants are encouraged to apply earlier)

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Position of Lecturer/Senior Lecturer/Reader in Mathematics, University of Sussex
by Enrico Scalas 10 Jul '17

10 Jul '17

Car* Collegh*, al Dipartimento di Matematica dell'Universita' del Sussex stiamo reclutando in probabilita' e statistica. Vi prego di diffondere l'annuncio se conoscete persone interessate. I link sono: http://www.sussex.ac.uk/about/jobs/lecturer-senior-lecturer-in-mathematics-… http://www.jobs.ac.uk/job/BCQ418/lecturer-senior-lecturer-or-reader-in-math… Il profilo e': Applications are invited from all areas of mathematics strengthening and complementing the Department's research portfolio. Applications are particularly welcome from probability and statistics including, for example, mathematical statistics, rigorous data science, stochastic analysis, processes in random environments, and probabilistic modelling. Il bando contiene poi i link a "job description" e "person specification". Grazie per l'attenzione e cordiali saluti, Enrico Scalas Professor of Statistics and Probability Head of Department, Mathematics University of Sussex, UK

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deadline early-bird registration to the 11th ClaDAG Conference
by Francesca Greselin 10 Jul '17

10 Jul '17

---- We apologize for cross posting ---- Dear all, this is just a friendly reminder that *today* is the deadline for early-bird registration to the *11th Scientific Meeting of the CLAssification and Data Analysis Group of the Italian Statistical Society * http://www.cladag2017.unimib.it/ For the 2017 edition of the Conference, the University of Milano-Bicocca, Bocconi University, Politecnico di Milano, University of Milano and Università Cattolica del Sacro Cuore are cooperating and supporting the event, that will be hosted at University of Milano-Bicocca. *Papers* Around 150 papers have been submitted for the Conference, for which the usual blind referee process has been carried out by the Scientific Program Committee, chaired by Francesco Mola. *Keynote speakers:* - J. Sunil Rao, <http://www.biostat.med.miami.edu/people/primary-faculty/sunil-rao> Division of Biostatistics, Department of Public Health Sciences University of Miami, Florida, USA, - *Classified Mixed Model Prediction*- Antony Davison, <http://statwww.epfl.ch/davison/davison.html> Institute of Mathematics, Ecole Poytechnique Federale de Lausanne, Switzerland - *Statistical models for complex extremes*- Roberto Rocci <http://economia.uniroma2.it/faculty/145/rocci-roberto>, Dipartimento di Economia e Finanza, Università degli studi di Tor Vergata, Rome, Italy - *An URV approach to cluster ordinal data* *Young researchers data challenge*Young researchers are invited to a data challenge, at Politecnico di Milano the day before the Conference, say on September 12, and sponsored by Oracle and Data Reply. Amazing prices are announced for the winners! *Statistical Challenges in Big Data & Complex Systems* A satellite Conference will take place on Tuesday September 12, at the University of Milano. More information will be available soon at http://www.cladag2017.unimib.it/ *Social dinner*The social dinner will take place on September 14th, in the *San Nazaro Porch* of the ancient “*Cà Granda*” complex, entrusted to the Tuscan architect Antonio Averlino, known as Filarete. Founded on 12 April, 1456 by the Duke of Milan Francesco Sforza and his wife Bianca Maria, the gigantic complex was built to provide medical care for the city’s poorest people. *Conference Proceedings* The Conference Proceedings will be published in digital edition with ISBN and distributed for free to all the Cladag2017 Participants. *Post conference publications* After the Conference, the Program Committee encourages authors of the best papers to submit an extended version for possible publication in the *Springer Series:* "Studies in Classification, Data Analysis, and Knowledge Organization", or alternatively to submit to a *special issue* of the following journals: Statistical Analysis and Data Mining <http://www.statisticsviews.com/details/journal/2285261/Statistical-Analysis…>, published on behalf of the American Statistical Association <http://www.amstat.org/>, and Statistics and Applications <http://statisticaeapplicazioni.vitaepensiero.it/> Both journals will offer the possibility to publish a selection of the best 10-15 papers presented at CLADAG 2017. Topics covered in these papers should be in line with the aims and scope of the journal and will undergo a regular review process. We look forward to see you in Milan on 12-15 September for CLADAG 2017! The organizing Committee

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