Saarland University, Germany (Coordinator)
University of Lorraine, France
Charles University, Czech Republic
University of Malta, Malta
University of Trento, Italy
University of Groningen, Netherlands
University of the Basque Country, Spain

European Master's Program in Language and Communication Technologies (LCT)

Summary of Study Programme:

The modular curriculum consists of four components:

(A) Core modules ensure that the students obtain a solid common foundation designed to cover all areas necessary for working in LCT, including theoretical as well as practical skills; the number of credits for the various modules differs depending on the students’ background. Core modules are normally taken during the first year.

(B) Specialized modules complement the common core to help build a personalized profile. As a sample of possible profiles, we give guidelines for three tracks that suit different incoming backgrounds and prepare students for different career possibilities. The tracks are purely advisory: it is not mandatory to follow any specific track and they are not shown on final certificates. They are meant to help design a personal path through the structure of the programme.

The three suggested tracks are characterized as follows:

The Digital Language Resources (DLR) track equips students having a strong linguistics background with the kind of insights and practical skills required to design, create and exploit annotated data resources for natural language applications or for the empirical validation of issues in cognitive and experimental linguistics.

The Natural Language Algorithms and Applications (NLA) track, intended mainly for students with a computer science background, revolves around the design and implementation of algorithms and machine learning techniques that are relevant to fundamental natural language processing problems such as parsing, generation, translation, as well as more advanced applications and platforms that make use of such algorithms.

The Language Data Science (LDS) track is aimed at students with a strong background in computer science and mathematics, familiar with AI approaches. It focuses on the application of Data Science techniques to large quantities of language data of different types and granularities in order to address important practical tasks such as information extraction, sentiment analysis, speech recognition, data visualisation etc.

It is of course possible to mix and match courses from different tracks to provide a more individually-tailored course of study to each student.

(C) Free choice courses, soft skills courses and an internship offer, respectively, the opportunity to acquire additional specialized topics reflecting current trends and hot research and employment areas, improve soft skills and gain practical experience and contact with the world of work in a company or in a research lab within or outside the university partners.

(D) Joint programme events are occasions during which students acquire additional (hard and soft) skills and have opportunities for networking with other students and with the associated partners. The internal summer school takes place before the start of each academic year, whereas the annual meeting is in the spring.

(E) Master thesis rounds off the learning experience with an independent project, which can be carried out at the university or as an internship. Modules and learning outcomes The LCT curriculum consists of coursework and an internship (90 ECTS) plus a Master thesis (30 ECTS). Courses are primarily distributed over the first three semesters, while most of the work on the Master thesis is completed in the fourth semester.

This results in a 2-year programme of 120 ECTS. The students study one year each at two universities of the consortium. The benefits of such a programme are twofold:

(a) scientifically, it brings students in contact with two different research environments and different areas of specialization; and
(b) culturally, it brings students in contact with two different societies which, crucially in our case, also mainly do research on (at least) two different languages (given the topic of the Masters, multilinguality is considered a key issue).


Admission requirements

Bachelor degree or equivalent in the area of (Computational) Linguistics, Language Technology, Cognitive Sciences, Computer Science, Mathematics, Artificial Intelligence, or other relevant disciplines

Language: Toefl at least 95 overall, IELTS at least 7.0, Cambridge Advanced at least B, Cambridge Proficiency at least pass


The Partner Universities

The European Masters Program in Language and Communication Technologies (LCT) is an international distributed Master of Science/Arts course. Each student studies at two of the partner universities. The program is offered by the following consortium of partners:

Saarland University, Germany (Coordinator)

University of Lorraine, France

Charles University, Czech Republic

University of Malta, Malta

University of Trento, Italy

University of Groningen, Netherlands

University of the Basque Country, Spain

More information on the local implementation of the program at each respective partner site is found here:
https://lct-master.org/contents_2014/consortium.php