Master's Degree Programme in Bayesian Statistics and Decision Analysis (EuroBayes)
The Programme provides advanced training for students who wish to develop special skills in the modern methodologies of statistical data analysis, with a particular emphasis on Bayesian inference. The programme is implemented as a joint effort of four European universities, representing a wide spectrum of different orientations of study and corresponding profiles of research. The partner universities responsible for the programme are: the University of Helsinki, Université Paris-Dauphine (Paris, France), Università La Sapienza (Rome, Italy), Alpen-Adria-Universität Klagenfurt (Klagenfurt, Austria). It is possible to negotiate one semester study period to some of the participating European Universities. The topic of the Master thesis is usually chosen to correspond to a genuine research problem, and is then based on real data.
Statistical data analysis can be seen as a systematic, predominantly quantitative approach towards acquiring an improved understanding of some studied phenomenon if interest, or also, as a means for making informed rational decisions. Both these aspects generally involve some degree of uncertainty. The statistician's task is then to explain such uncertainty, and to reduce it to the extent this may be possible in the given context.
One way of looking at statistics stems from the perception that, ultimately, probability is the only appropriate way to describe and systematically deal with uncertainty. The scientific discipline based on this understanding is called Bayesian Statistics. In principle, Bayesian statistics is designed to handle all situations where uncertainty is found. Since some degree of uncertainty is present in almost every aspect of life, it may be argued that Bayesian statistics should be appreciated and used by everyone. The Bayesian paradigm has indeed experienced a spectacular growth during the past 10 years, and is still finding new areas of fruitful practical application. This development can be largely attributed, on one hand, to the increasing need of sophisticated, often hierarchical models to describe available data, which are typically much too complex for conventional statistics to handle, and on the other, to the development of powerful Markov Chain Monte Carlo (MCMC) integration techniques, which make it possible to come up with concrete numerical results from the Bayesian analysis. This has created an acute need for people who are well trained in Bayesian methodology and, as a consequence, extremely attractive opportunities for employment.
CALL FOR APPLICATIONS TO STUDIES STARTING AUTUMN 2014
Application period begins: 2 December 2013
Application deadline: 31 January 2014 at 16:15 Eastern European Time (GMT+2).
Eligibility to apply
To be eligible to apply You need to hold a Bachelor or equivalent degree in a suitable field, or have the degree completed before 31 July 2014. In addition, you must have completed a total of at least 80 ECTS compatible credits in mathematics and/or statistics. Relevant Bachelor's degrees include, in addition to mathematics and statistics, science and engineering degrees completed at universities and other institutions of higher education.
Admission will be based on the academic record, scope, and quality of previous studies in mathematics, English proficiency, and a motivation letter.
A letter of motivation should state why you want to study in the Master's Degree Programme in Bayesian statistics and decision analysis. You need to provide a short curriculum vitae as a part of the letter of motivation.
Proficiency in English
You need to be proficient in English language when applying to the programme. Your earlier degree can work as a certificate in some cases: If you have studied at a Finnish university and your degree includes compulsory studies in English, you fulfill the language requirements. Also if your earlier degree is instructed in English in EU or EEA Countries, or in Australia, Canada, New Zealand, or the U.S.A., you may be exempted from the language test. Otherwise you need to submit a language test score.
Before submitting your application, please see the following page for further information on language requirements, acceptable language tests and minimum scores:
Required language skills at University of Helsinki
University of Helsinki arranges language tests for applicants living in Finland.
There will be no entry examination. Student selection is based on the application papers.
Instructions on how to prepare your application are given on the international admission page of University of Helsinki
The page contains a link to an online application service where you will fill in an online registration form. In addition you will need to submit an application form with the required enclosures by regular mail.
A maximum of eight students will be admitted to the Master's Degree Programme in Bayesian Statistics and Decision Analysis.
Students admitted to the Master's Degree Programme in Bayesian Statistics and Decision Analysis (EuroBayes) at the Faculty of Science will study for a Master of Science degree in statistics consisting of 120 ECTS-compatible credits. The target schedule for completing this degree is two years. The language of instruction is English.
The following curriculum applies for the students of the Master's Degree Programme in Bayesian Statistics and Decision Analysis (EuroBayes) starting their studies in 2012 and are applicable to students having started since 2007.
MASTER OF SCIENCE DEGREE (120 CREDITS)
57554 ADVANCED STUDIES IN BAYESIAN STATISTICS AND DECISION ANALYSIS (minimum of 114 CR)
57059 Markovian modeling and Bayesian learning, 5cr
57744 Bayesian theory with applications, 5cr
57733 Computational statistics, 8cr
57710 Software tools for statisticians, 5-10cr (This course is not in teaching curriculum any more and is thus not a compulsory requirement.)
78185 Generalized Linear Models, 6-8 cr (This course can be taken as an exam, see here. It is also possible to take this course instead.
57632 Master's thesis, 40 cr, containing
50041 Maturity test
Optional courses in statistics, bioinformatics, mathematics, computer science, or other disciplines in accordance with an approved personal study plan (FM-HOPS)
OTHER STUDIES, COMPULSORY (minimum of 6 CR)
57599 Personal study plan (FM-HOPS), 1 cr
57592 Advanced internship or orientation studies, 1-3 cr
993734 Academic Writing for Students in English-Medium Master’s Degree Programmes 1, 2 cr
993735 Academic Writing for Students in English-Medium Master’s Degree Programmes 2, 2 cr
Studies to satisfy the following language requirements specified in Section 11 of the Regulations on Degrees at the Faculty of Science: Students who have completed their basic and secondary education in Finnish or Swedish must complete studies in the second national language and demonstrate a good command of their native language by passing the maturity test as part of their Bachelor’s or Master’s degree. (In Finnish) Mikäli hakija on saanut suomen- tai ruotsinkielisen koulusivistyksen, häntä koskevat seuraavat tutkintosäännön 11 §:n kielitaitovaatimukset: Opiskelijan on suoritettava toisen kotimaisen kielen opinnot ja osoitettava kypsyysnäytteellä äidinkielen taito osana alempaa tai ylempää korkeakoulututkintoa.
As stated in Section 5 of the Regulations on Degrees at the Faculty of Science, the degree language is English given that Master’s thesis and at least 50 cr of the studies are taken in English. It is also possible to write Master’s thesis in Finnish or in Swedish and then the degree language will be recorded accordingly.
Here is a list of Master's theses which have been accepted in this Master's Degree Programme.
Approximating posterior distributions over dendrogram spaces with an application to population genetics
Inductive inference in supervised classification
Linear models with regularization
Bayesian confirmatory factor analysis for detection of differential gene expression
A comparison of methods for haplotype inference
The Bayesian paradigm has indeed experienced a spectacular growth during the past 10 years, and is still finding new areas of fruitful practical application. This development can be largely attributed, on one hand, to the increasing need of sophisticated, often hierarchical models to describe available data, which are typically much too complex for conventional statistics to handle, and on the other, to the development of powerful Markov Chain Monte Carlo (MCMC) integration techniques, which make it possible to come up with concrete numerical results from the Bayesian analysis. This has created an acute need for people who are well trained in Bayesian methodology and, as a consequence, extremely attractive opportunities for employment.
The Student Affairs Office of the Faculty of Science, P.O. Box 44, Jyrängöntie 2, 00014
University of Helsinki, Finland, tel. +358 9 191 50066 or +358 9 191 50065, office hours:
Mon-Fri from 10 a.m. to 3 p.m., email: email@example.com, web address:
Coordinator of the Master's degree programme: Sirkka-Liisa Varvio, University Lecturer, email:
sirkka-liisa.varvio 'at' helsinki.fi, tel. +358 9 191 51405.International Programmes at UH