Events
April
2019
May
2019

Structure and contents

The Master in Computational Science (MCS) program is an exciting new approach to understanding complex systems in a broad range of knowledge areas including the natural and physical sciences, the social sciences, the life sciences, management science and medical science. By integrating computer simulation, mathematical modeling, numerical analysis, and data analysis, recent developments in computational science are making possible what was unthinkable only few years ago. Problems that are inaccessible to traditional experimental and empirical methods can now be addressed thanks to new techniques in algorithmic modeling and the increasing speed of modern supercomputers.

The MCS program combines courses from computer science, mathematics, statistics and data analysis to build application-oriented competences in simulation science and data science. Students enrolled in the MCS program acquire valuable and much sought-after analytical skills through direct involvement in modeling projects addressing a wide range of real-world problems spanning many interdisciplinary applications.

The program introduces students to the university's blend of innovative scientific research and real world applications, thus providing an excellent foundation for a career in industry and science. Students may emphasize numerical software, mathematical modeling, deterministic and probabilistic theory, computer simulation, or data science. Our graduates are ready to pursue professional careers in research, engineering, scientific computing, data science, data and business analytics, computational medicine, and information systems.

For the master's thesis, students can participate in ongoing research projects at the ICS,  the IDIDS, or the Faculty of Informatics. Topics include Numerical Analysis, High-Performance Computing, Geo-Science, Computational Engineering, Optimization, Computational (Bio-) Mechanics and Fluid-Mechanics, Computational Medicine, Drug-Design, Computational Finance, or Shape Analysis. Interested students will also be given the possibility to participate in ongoing research projects. Elective courses and the master thesis allow students to tailor their learning experience to their individual interests and professional objectives while creating innovative combinations of knowledge across multiple disciplines.

Expand All

  • Study Programme

    The Master of Science in Computational Science programme consists of four semesters of full-time study (120 ECTS). It offers courses in numerical mathematics and computer science, together with a wide range of more application-oriented courses. It finishes with a master’s thesis in the form of a half–year project, worth 30 ECTS, which can be carried out in an industrial or research setting. Selected block courses are taught by distinguish professors from other prominent academic institutions and international research centres, e.g., Stanford, University of Erlangen, University of Texas at Austin, The University of British Columbia, or Massachusetts Institute of Technology (MIT).

    With the guidance of the Master Director, students will be encouraged to set up an individual study plan that includes appropriate elective courses. The Master Director will advise and accompany students through the entire two-year course of study.

     

    First Semester

    Mandatory (27 ECTS)

    High-Performance Computing

    6

    Introduction to Ordinary Differential Equations

    3

    Introduction to Partial Differential Equations

    6

    Numerical Algorithms

    6

    Introduction to Data Science

    6

    Electives (3 ECTS)

    Software Atelier: Partial Differential Equations

    3

    Software Tools in Computational Science

    3
       

    Second Semester

     

    Mandatory (24 ECTS)

     

    Advanced Discretization Methods

    6

    Multiscale Methods

    6

    Software Atelier: Simulation, Data Science & Supercomputing

    6

    Stochastic Methods

    6

    Electives (6 ECTS)

     

    Advanced Computer Architectures

    6

    Bioinformatics

    6
    Functional and Numerical Analysis (FOMICS block course)

    6

    Geometric Algorithms

    6

    Graphical Models and Network Science

    6

    Introduction to Network Science

    6

    USI-CSCS Summer School on Effective High Performance Computing

    6
       

    Third Semester

     

    Mandatory (30 ECTS)

     

    Computational Biology and Drug Design*

    6

    Data Assimilation*

    3

    Generalizations of the Linear Model*

    3

    Machine Learning

    6

    Molecular Dynamics and Monte Carlo Methods

    6

    Preparation Master's Thesis

    6
       

    Fourth Semester

     

    Mandatory (24 ECTS)

     

    Master Thesis

    24

    Electives (6 ECTS)

     

    Advanced Computer Architectures**

    6

    Bioinformatics** 

    6

    Computer Vision & Pattern Recognition*/**

    6

    Functional and Numerical Analysis (FOMICS block course)

    6

    Geometric Algorithms**

    6

    Geometric Deep Learning*/**

    6

    Graphical Models and Network Science**

    6

    Introduction to Network Science**

    6

    USI-CSCS Summer School on Effective High Performance Computing**

    6

    * The course is not offered in the academic year 2018/19

    ** If not already taken in the 1st year

    Please be aware that slight changes in the study programme may occur.

  • Teaching

    Top-level faculty of international renown teach innovative courses, with a strong multi-disciplinary orientation and in collaboration with prestigious institutions at local and international level. Teaching at the Faculty of Informatics emphasizes close contact between students and staff. Professors are pursuing research on a variety of topics and are active participants in Swiss and international research projects and networks. Visiting professors from renowned universities complement the top-quality teaching.
    The Institute of Computational Science in the Faculty of Informatics aims to train experts that are interdisciplinary in approach, with abstract mathematical skills, a sound knowledge in numerical methods and computational science, as well as project-management and teamwork abilities.

    Academic Directors: Prof. Olaf Schenk and Prof. Ernst Wit

    Prof. Michael Bronstein received the Ph.D. in computer science (2007) from the Technion in Israel. His main research interests are geometric methods in computer vision, pattern recognition, and computer graphics. Prof. Bronstein's research was featured in international news and recognized by several awards, including the prestigious ERC grant (2012). He has served on program committees of major conferences in his field and was keynote speaker in numerous international symposia. Prof. Bronstein is also actively involved in technology transfer and consulting. His start-up track record includes Novafora (2004-2009 as co-founder and VP of video technology) and Invision (2009-2012 as one of principle technologists). Since the acquisition of Invision by Intel in 2012, Michael has also served as a Research Scientist at Intel, where he was one of the key algorithm developers for the RealSense 3D sensor.

    Website or personal page: Prof. Michael Bronstein 
    Courses: Computer Vision & Pattern Recognition

    Prof. Illia Horenko is an associate professor in the faculty of informatics and the Institute of Computational Science of the University of Lugano. He received a Ph.D. in applied mathematics from the Free University (FU) of Berlin in 2004 and spent several years as a postdoctoral research fellow at the Biocomputing Group and Climate Research Group at the FU Berlin, before joining the faculty of mathematics and computer science of the FU Berlin as an assistant professor in 2008. His research interests are focused on the development and practical implementation of data analysis algorithms and time series analysis approaches. Published applications of the methods developed by I. Horenko include problems from climate research, economics, biophysics, engineering and sociology. Prof. Horenko has published over 40 papers in the professional literature. He was a co-organizer of several big scientific programs and is a frequent reviewer for international funding agencies and the top journals in his field.

    Website or personal page: Prof. Illia Horenko
    Courses: Deterministic Methods, Stochastic Methods

    Prof. Kai Hormann is a full professor in the Faculty of Informatics at USI. He received a PhD in computer science from the University of Erlangen in 2002 and spent two years as a postdoctoral research fellow at Caltech in Pasadena and the CNR in Pisa, before joining Clausthal University of Technology as an assistant professor in 2004. During the winter term 2007/2008 he visited Freie Universität Berlin as a BMS substitute professor and came to Lugano as an associate professor in 2009. His research interests are focussed on the mathematical foundations of geometry processing algorithms and their applications in computer graphics and related fields. In particular, he is working on generalized barycentric coordinates, subdivision of curves and surfaces, barycentric rational interpolation, and dynamic geometry processing. Professor Hormann has published over 60 peer-reviewed papers and is an associate editor of Computer Aided Geometric Design, Computers & Graphics, and the Dolomites Research Notes on Approximation.

    Website or personal page: Prof. Kai Hormann
    Course: Numerical Algorithms

    Prof. Rolf Krause is chair of advanced scientific computing and the director of the institute of computational science in the faculty of informatics. From 2003 to 2009, he was professor at the University of Bonn. During that time he spent a sabbatical at UC San Diego (USA) and Columbia University New York (USA). In 2002 he was on a Postdoctoral research visit at the Courant Institute (NYU, New York). He holds a Diploma and a PhD (2000) in Mathematics from the FU Berlin (Germany). His research focuses on numerical simulation and mathematical modeling in scientific computing and computational sciences, in particular the development of theoretical well founded simulation methods, which show excellent performance also in real world applications. He was an associate editor of the SIAM Journal on Scientific Computing (SISC).

    Website or personal page: Prof. Rolf Krause
    Courses: Introduction to Ordinary Differential Equations, Introduction to Partial Differential EquationsMultiscale Methods

    Prof. Igor Pivkin received his B.Sc. and M.Sc. degrees in Mathematics from Novosibirsk State University, Russia, M.Sc. degree in Computer Science and Ph.D. in Applied Mathematics from Brown University, USA. Before coming to Lugano, he was a Postdoctoral Associate in the Department of Materials Science and Engineering at Massachusetts Institute of Technology, USA. The research interests of Igor Pivkin lie in the area of multiscale/multiphysics modeling, corresponding numerical methods and parallel large-scale simulations of biological and physical systems. Specific areas include biophysics, cellular and molecular biomechanics, stochastic multiscale modeling, and coarse-grained molecular simulations.

    Website or personal page: Prof. Igor Pivkin
    Course: Advanced Discretization Methods

    Prof. Vittorio Limongelli took his Master Degree in Chemistry and Pharmaceutical Technology at University of Napoli "Federico II" (Italy) in 2004 and took at the same university his PhD degree in 2007. During those years, his research was focused on standard computational methodologies (e. g. molecular docking, homology modeling) applied to the study of systems of biopharmaceutical interest. In 2007 he was visiting PhD first at University of Bologna (Italy) and then at ETH Zurich (Switzerland). Here he did his PostDoc working in the field of enhanced sampling simulations used to study rare events in biosystems with a special focus on molecular binding processes. In December 2010 he got a permanent position as Researcher at the University of Naples "Federico II" (Italy) and in 2014 he got the qualification to function as Associate Professor in Italian Universities. From 2018 he is Professor in Computational Biology and Pharmacology at the Faculty of Biomedical Sciences of USI Lugano.

    Website or personal page: Prof. Vittorio Limongelli
    Course: Bioinformatics, Computational Biology and Drug Design

    Prof. Michele Parrinello is currently Professor at ETH Zurich, and the Università della Svizzera italiana Lugano, Switzerland. He is known for his many technical innovations in the field of atomistic simulations and for a wealth of interdisciplinary applications ranging from materials science to chemistry and biology. For his work he has been awarded the 2011 Prix Benoist and many others prizes and honorary degrees. He is a member of numerous academies and learned societies, including the National Academy of Science, the British Royal Society and the Italian Accademia Nazionale dei Lincei. He is the author of more than 600 papers and his work is highly cited.

    Website or personal page: Prof. Michele Parrinello

    Prof. Evanthia Papadopoulou is an associate professor of computer science at the Università della Svizzera italiana. From 1996 to 2008 she was a research staff member at the IBM T.J. Watson research center, Yorktown Heights NY, USA. She had also been a Faculty member in the department of computer science at the Athens University of Economics and Business. She holds a BS degree in mathematics from University of Athens, an MS in computer science from University of Illinois at Chicago, and a Ph.D. in computer science from Northwestern University, USA, December 1995. Her research interests include the design and analysis of discrete algorithms, computational geometry and its applications, software and implementation of geometric algorithms, data structures, and algorithmic aspects of VLSI computer-aided design. For her work on "Voronoi diagram based VLSI Critical Area Analysis", she received the IBM outstanding innovation award, August 2006, and a rating of Technical Accomplishment for IBM Research, December 2006.

    Website or personal page: Prof. Evanthia Papadopoulou
    Course: Geometric Algorithms

    Prof. Olaf Schenk is an associate professor at the Institute of Computational Science within the Department of Informatics at the Universita della Svizzera italiana, Switzerland. He graduated in Applied Mathematics from Karlsruhe Institute of Technology (KIT), Germany, and earned his PhD in 2001 from the Department of Information Technology and Electrical Engineering of ETH Zurich and a venia legendi from the Department of Mathematics and Computer Science from the University of Basel in 2009. He conducts research in applied algorithms, computational science, and software tools for high-performance scientific computing. Olaf Schenk is a member of SIAM, and ACM, and a senior member of IEEE. He is a recipient of an IBM faculty award (2008) and two leadership computing awards from the U.S. Department of Energy (2012, 2013). He serves on the editorial board of the SIAM Journal for Scientific Computing and on the project leadership team of the Swiss Platform for Advanced Scientific Computing PASC. He has been elected as the Program Director for the SIAM Activity group on Supercomputing in the period 2016-2017.

    Website or personal page: Prof. Olaf Schenk
    Courses: High-Performance Computing, Software Atelier: Simulation, Data Science & Supercomputing

    Prof. Jürgen Schmidhuber is Director of the Swiss Institute for Artificial Intelligence IDSIA (since 1995), Professor of Artificial Intelligence at the University of Lugano, Switzerland (since 2009), Head of Cognitive Robotics in the Faculty of TUM Computer Science at TU Munich, Germany (since 2004, as Professor Extraordinarius until April 2009), and Professor SUPSI, Switzerland (since 2003). He obtained his doctoral degree in computer science from TUM in 1991 and his Habilitation degree in 1993, after a postdoctoral stay at the University of Colorado at Boulder, USA. He helped to transform IDSIA into one of the world´s top ten AIlabs (the smallest!), according to the ranking of Business Week Magazine. He is a member of the European Academy of Sciences and Arts, and has published more than 200 peer-reviewed scientific papers on topics such as machine learning, mathematically optimal universal AI, artificial curiosity and creativity, artificial recurrent neural networks, adaptive robotics, complexity theory, digital physics, theory of beauty, and the fine arts.

    Website or personal page: Prof. Jürgen Schmidhuber
    Course: Machine Learning 

    Prof. Patrick Gagliardini studied at the Polytechnical School in Zurich (ETHZ) where he graduated in Physics in 1998. In January 2003 he received a PhD from the Faculty of Economics of USI for a thesis in Econometrics. In 2003 he has been a visiting fellow at the Laboratoire de Finance-Assurance of CREST (Paris) with a SNSF research grant. Between 2004 and 2006 he held an assistant professor position at the Faculty of Economics of the University of St. Gallen. Since 2012 he is full professor of Econometrics at USI. His research interests focus on econometrics and financial econometrics. He has published research papers on topics such as large panel factor models, nonparametric estimation, the Generalized Method of Moments in asset pricing, time series analysis, and credit risk.

    Website or personal page: Prof. Patrick Gagliardini
    Course: Econometrics

    Prof. Antonietta Mira is co-founder and co-director of the InterDisciplinary Institute of Data Science , IDIDS at USI where she also served as the Vice-Dean in the Faculty of Economics (2013-2015) and is a professor of statistics at the Institute of Finance at USI. She is a fellow of the International Society for Bayesian Analysis (ISBA), a visiting fellow of the Isaac Newton Institute for Mathematical Sciences at Cambridge University. (2014 and 2016) and has been a visiting professor at Université Paris-Dauphine, University of Western Australia, Queensland University of Technology, Brisbane, and University of Bristol, UK. Her current research focuses on data science and methodological and computational statistics, both of which have a clear interdisciplinary scope across social science, finance, economics and industry. She is often invited to talk at international scientific conferences where she also organizes sessions on topics related to her research interests. She serves on the editorial board of high impact scientific journals such as Statistica Sinica (2005-8), Journal of Computational and Graphical Statistics (2006-8), Bayesian Analysis (2008-16) and as guest editor of special issues (2014-15-16). Antonietta holds a PhD in Computational Statistics (1998) and a Master¹s in Statistics (1996) from the University of Minnesota in Minneapolis, US. She also has a Doctorate in Methodological Statistics from the University of Trento (1995), Italy, and earned her Bachelor¹s in Economics, summa cum laude, from the University of Pavia, Italy.

    Website or personal page: Prof. Antonietta Mira
    Course: Introduction to Statistics

    Dr. Spyros Angelopoulos is a Data / Network Scientist, working currently at the InterDisciplinary Institute of Data Science - IDIDS at USI. He holds a PhD in Information Systems and Management from Warwick Business School in the UK, a Diploma (Dipl-Eng, equivalent to MEng) in Production Engineering and Management, as well as an MSc in Management Engineering from the Technical University of Crete, Greece. His current research is on the emergence and evolution of social networks within online communities. His research interests include Social Networks, Big Data Analytics, and Cloud Computing.

    Website or personal page: Dr. Spyros Angelopoulos
    Course: Simulation & Data Sciences Seminar

    Dr. Maksym Byshkin is a Swiss National Science Foundation postdoctoral research fellow in the Social Network Analysis Research Centre (SoNAR-C) at the Institute of Computational Sciences (ICS) and the InterDisciplinary Institute of Data Science (IDIDS), Università della Svizzera italiana (USI). His research fields are statistical physics, statistical network analysis, computational chemistry and interdisciplinary collaborations. The research activity and research interests are focused on developments of empirical models and computational methods for high performance computing.

    Website or personal page: Dr. Maksym Byshkin
    Course: Simulation & Data Sciences Seminar

    Dr. Drosos Kourounis is a senior researcher at the Institute of Computational Science within the Faculty of Informatics at the Università della Svizzera italiana Lugano, Switzerland. He graduated in Electrical Engineering from the Aristotle University of Thessaloniki, Greece, and earned his PhD in 2008 from the Department of Material Science and Engineering of University of Ioannina, Greece. He worked as a post doctoral fellow at the department of Energy Resources Engineering of Stanford University on optimization of compositional reservoir flow in porous media. His research now focuses on inverse problems that emerge in reservoir modeling, seismic imaging and smart grids and it involves the development of associated high-performance algorithms and software tools.

    Website or personal page: Dr. Drosos Kourounis
    Course: Software Atelier: Partial Differential Equations

     

    External Distinguish Lecturers

    Petros Koumoutsakos is Professor of Computational Science at ETH Zurich (2000-.). He received his Diploma (1986) in Naval Architecture at the National Technical University of Athens and a Master’s (1987) at the University of Michigan, Ann Arbor. He received his Master’s (1988) in Aeronautics and his PhD (1992) in Aeronautics and Applied Mathematics from the California Institute of Technology. He conducted postodoctoral studies at the Center for Parallel Computing (Caltech, 1992-1994) and at the Center for Turbulence Research (Stanford U./NASA Ames, 1994-1997). Petros has been elected Fellow of the American Society of Mechanical Engineers (ASME), the American Physical Society (APS) and the Society of Industrial and Applied Mathematics (SIAM). He is  recipient  the Advanced Investigator Award by the European Research Council and led the team that won the ACM Gordon Bell prize in Supercomputing (2013). In 2016 he was elected Fellow of the Collegium Helveticum.

    Website or personal page: Prof. Petros Koumoutsakos
    Courses: Simulations Using Particles: from DNA to the Universe (offered in Spring 2018)

    Dominik Obrist holds a degree in mechanical engineering of the ETH Zurich and earned his doctoral degree in 2000 at the Department of Applied Mathematics of the University of Washington (Seattle, USA). From 2000 to 2005, he worked in various positions for the supercomputer company Cray Inc. In 2005, Dominik Obrist returned to academics as a senior researcher (Oberassistent) at the Institute of Fluid Dynamics of ETH Zurich. Next to his work in the fields of aeroacoustics, hydrodynamic stability theory and numerical modelling, he established a research group for biomedical fluid dynamics. In 2011, Dominik Obrist earned the venia legendi (Habilitation) at ETH Zurich with a treatise on the fluid mechanics of the inner ear. In 2013, he was appointed as Professor for Cardiovascular Engineering at the ARTORG Center for Biomedical Engineering Research of the University Bern. His present research activities encompass several aspects of cardiovascular fluid mechanics (e.g. aortic valves, microcirculation) as well as other biomedical flow systems (e.g. gastric mixing, respiratory flow).

    Website or personal page: Prof. Dominik Obrist
    Courses: Computational Fluid Dynamics (offered in Fall 2017)

    Michael Saunders from Stanford holds a PhD in Computer Science from Stanford University. Since 1987 he has been a Professor in Operations Research at Stanford specializing in numerical algorithms for sparse linear systems and large-scale constrained optimization. He is coauthor of the linear equation solvers SYMMLQ, MINRES, LSQR, LSMR, LUSOL, LUMOD, LSRN and the optimization solvers MINOS, LSSOL, NPSOL, QPOPT, SNOPT, SQOPT, PDCO. He is an Honorary Fellow of the Royal Society of New Zealand (2007) and a SIAM Fellow (2013). In 2012 he won the SIAM Linear Algebra Prize and was elected to the Stanford University Invention Hall of Fame.

    Website or personal page: Prof. Michael Saunders
    Courses: Large-Scale Optimization (course will be offered on a bi-yearly basis)

    Gerhard Wellein from University of Erlangen holds a PhD in Solid State Physics from the University of Bayreuth and is Professor for HPC at the Department for Computer Science at University of Erlangen-Nuremberg. He heads the HPC group at Erlangen Regional Computing Center (RRZE) and has more than ten years of experience in teaching HPC techniques to students and scientists from Computational Science and Engineering. His research interests include solving large sparse eigenvalue problems, novel prarallelization approaches, performance modeling and engineering, and architecture-specific optimization. Together with G. Hager and J. Treibig he is the recipient of the 2011 Informatics Europe Curriculum Best Practices Award in recognition of the outstanding educational initiative Teaching High Performance Computing to Scientists and Engineers: A Model-Based Approach.

    Website or personal page: Prof. Gerhard Wellein
    Courses: Node-Level Performance Engineering (course will be offered on a bi-yearly basis)

    Georg Hager holds a PhD in Computational Physics from the University of Greifswald. He is a senior researcher in the HPC Services group at Erlangen Regional Computing Center (RRZE) at the University of Erlangen-Nuremberg. Recent research includes architecture-specific optimization strategies for current microprocessors, performance engineering of scientific codes on chip and system levels, and special topics in shared memory and hybrid programming. His daily work encompasses all aspects of user support in High Performance Computing like tutorials and training, code parallelization, profiling and optimization, and the assessment of novel computer architectures and tools. His textbook "Introduction to High Performance Computing for Scientists and Engineers" is recommended or required reading in many HPC-related lectures and courses worldwide. In his teaching activities he puts a strong focus on performance modeling techniques that lead to a better understanding of the interaction of program code with the hardware.

    Website or personal page: Dr. Georg Hager
    Courses: Node-Level Performance Engineering (course will be offered on a bi-yearly basis)

    Eldad Haber is a full professor in the Departments of Mathematics and Earth and Ocean Science, and the NSERC Industrial Research Chair in Computational Geoscience at the University of British Columbia. He is an associate editor of the SIAM Journal on Scientific Computing. His primary research interest is scientific computing and its application to geophysical and medical imaging.

    Website or personal page: Prof. Eldad Haber
    Courses: Computational Data-based Imaging (course will be offered on a bi-yearly basis)

    Sebastian Reich, Universität Potsdam, Germany and University of Reading
    Sebastian Reich is a Professor of Numerical Analysis at the University of Potsdam (full time) and the University of Reading (part time). He also holds an honorary visiting professorship at Imperial College London. Reich is the author of over 100 journal articles and the co-author of Simulating Hamiltonian Dynamics (Cambridge, 2005), which has received more than 600 citations. His research areas cover numerical analysis and scientific computing with applications to classical mechanics, molecular dynamics, geophysical fluid dynamics, and data assimilation. In 2003 he received the Germund Dahlquist Prize from the Society for Industrial and Applied Mathematics (SIAM) for his work on geometric integration methods.

    Website or personal page: Prof. Sebastian Reich
    Courses: Data Assimilation (offered in Fall 2017)

    Stefano Serra Capizzano received the "Laurea" in Computer Science in 1990 at the Pisa U. and the PhD in Applied Mathematics in 1996 and Optimisation at the Milano U., both with "summa cum laude". In 1996 he started as Researcher in Numerical Computing at the Department Of "Energetica" of Firenze U.; from 2000 to 2005 he was Associate Professor  at the CFM Department of "Insubria" U. in Como. Since October 1st 2006 he is Full Professor. He serves as head of the Department of Physics and Mathematics (up to September 30th 2011) and of the Department of Science and high Technology from October 1st 2011, and since October 1st 2007 to May 26th 2008 he was the representative of the heads of Departments in the Senate of Insubria U. Since May 27th 2008 to July 21st 2012 he served as Dean of the Faculty of Sciences - Como. His teaching activity in Italy and abroad includes courses at Master and PhD level. Moreover he was part of the Board for the E-learning project at the University level, he was in the Staff of the PhD Program of Milano (Computational Mathematics) and of Como - Insubria (Physics and Astrophysics). Since October 2007 he started a new PhD Program in Mathematics of Computing in the Insubria U.

    Website or personal page: Prof. Stefano Serra Capizzano
    Courses: Fast Solvers (offered in Spring 2017 and 2018)

  • Language

    Admission to English-language graduate-level (Master) programmes at USI require a good command of the English idiom. Non-English native speakers applying for such programmes, or whose previous degree was obtained in another language, are required to provide an internationally acknowledged language certificate equal to the B2 level, as defined by the Common European Framework of Reference for language learning (CEFR), or equivalent (e.g. TOEFL, IELTS, etc.).

    The B2 level on the CEFR corresponds to the following scores in internationally acknowledged exams:

    IELTS 5.5
    TOEFL Computer based: 183
    Internet based: 65
    Paper based: 513
    Cambridge English FCE (First Certificate English)
    TOEIC Listening & Reading: 785
    Speaking: 150
    Writing: 160

    Students admitted under the above mentioned condition (with the exception for the Master in Cognitive Psychology in Health Communication) must achieve a C1 competence in English within the maximum time required to obtain the Master's degree.
    The level can be certified either by attending a language course offered at USI during the Fall and Spring semester, and by taking the final exam, or by providing an internationally acknowledged language certificate*.

    *  The C1 level on the CEFR corresponds to the following scores in internationally acknowledged exams:

    IELTS 7.0
    TOEFL Internet based: 100
    Cambridge English CAE (Advanced certificate), grade C or above
    BEC (Business English), grade C or above
    TOEIC Listening & Reading: 945
    Speaking: 180
    Writing: 180

    Italian

    As Lugano is located in the Italian-speaking part of Switzerland, students might be interested in acquiring the basics in Italian.
    The Università della Svizzera italiana offers a free of charge Italian language course: further information can be found here.