Bachelor

Master

In the degree program, students work strongly application-oriented and system-oriented. They learn to think in an interdisciplinary way in larger system contexts and to design, specify, design, test and accept systems within a frequently larger international team. These include, the development of new defense and security systems, taking into account specific requirements, such as operability, special material and system properties such as security against eavesdropping or disruptibility, but also extreme climatic conditions, interoperability or robustness. The focus of the work is the interaction of individual components and modules to a holistic system or subsystem for military use or to improve civil security.

Internship is not mandatory, but is optional during studies. If possible, we recommend doing an internship.

English language skills at the level SLP 3332 (professional) is accepted as proof of language proficiency

Engineering Science

Helmut-Schmidt-Universität/Universität der Bundeswehr Hamburg

EMerald is a Master programme organised by four European Universities – University of Liège (ULiège), University of Lorraine (UL), Luleå University of Technology (LTU) and Technische Universität Bergakademie Freiberg (TUBAF). The programme is designed to focus on the following major aspects of Resources Engineering, Characterisation, Processing, Modelling and Management. The EMerald Master Programme has been designed to find the right balance between knowledge of resources (geology, landfills, urban mines, reserve characterisation and modelling) and process engineering techniques (comminution, sorting, preconcentration, extractive metallurgy and waste disposal). 

It is mandatory to do an internship. It is easier to find internship when it is mandatory. 3-6 months is most common.

The Semester contributions totaling 94.00 EUR must be paid each semester. It includes Students union fee 87.00 EUR and Student Council fee 7.00 EUR

EMerald Master in Resources Engineering

TU Bergakademie Freiberg

Data Science combine skills in Mathematics, Computer Science, Statistics and specific knowledge in an application domain. The Master programme is research oriented and should enable students to carry out scientific research projects autonomously. Moreover students are taught how to communicate their insights and reflect on the ethical impacts of collecting and analysing large amounts of data as well as the consequences of automated data driven decision making. Students  can choose between Computational Neuroscience, Bioinformatics, Medical Data Science and Digital Humanities as domains. 

The Semester contributions totalling 350.48 EUR must be paid each semester. It includes Administrative fee 75.00 EUR, Students body Contribution fee 14.00 EUR, Train semester ticket fee 92.44 EUR, Bus Semester ticket fee 50.90 EUR, Culture semester ticket fee 11.14 EUR and Student union fee 107.00 EUR

UNIcert II, NULTE-Certificates with at least level B2, at least one year of studying or working in an English-speaking country, an average grade of at least 8 points in the school subject English in the two years prior to acquiring the university entrance qualification is accepted as proof of language proficiency

Applied Data Science

University of Göttingen

Master of Science in Geoinformatics and Spatial Data Science program will develop the students problem-solving skills, analytic capabilities, and teach innovative and creative scientific research methods. Programme sets goal to educate students in the most Advanced techniques in geographic information processing.

The Semester contributions totalling 316.03 EUR must be paid each semester. It includes Student union fee 99.11 EUR, Supplementary student insurance fee 0.23 EUR, University Sports fee 1.40 EUR, Student body fee 11.75 EUR, University radio station fee 0.30 EUR, Semester ticket for cultural events fee 3.40 EUR and Semester ticket 199.84 EUR

English native speakers are exempt from proving language proficiency

Semester	International Students	EU Students
Summer	30 Nov	15 Jan
Winter	31 May	15 Jul

Geoinformatics and Spatial Data Science

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