European-track follows the semester 3 in Fall. For this semester, students mandatory follow the following courses:
- Study Project (10 ECTS)
- Basics & Methods in Humanities and Social Science (2 ECTS) and one course of at least 4 ECTS courses from basket Social Sciences, Innovation, and Digital Transformation.
- 12 ECTS at least of lectures grouped in the other baskets.
- Computational Neuroscience (CNS)
- Machine Learning (ML)
- Bioinformatique (BI)
Study Project “Digitization and Society” (10 ECTS)
Lecturer: Dr. Thomas Herrmann
Abstract: In the study project, ISI students in Bochum conduct an application project from start to finish, practicing skills such as programming, software design, critical thinking, project and time management, presentation of scientific results, interdisciplinary thinking and cross-cultural work. Each project concludes with a written report including a reflection on the methodical approach. The projects are done in teams of at least two students, possibly from different disciplines, i.e. one student from the ISI programme with one student from the Humanities or Social Sciences, to also practice team work and communication. A cooperation agreement with the City of Bochum guarantees that study projects can be conducted in suitable facilities of the city administration and its subsidiaries. In case of scarcity of places, projects may also be done in cooperation with other partners, e.g. from industry, but always with an application to topics of social innovation. RUB has a strong record of applied Computer Sciences in non-technical disciplines (currently strengthened by establishing 13 new tenure-track professorships). The project is facilitated by the Institute for Neural Computation in cooperation with various other departments, to include input from Anthropology, Philosophy of Communication, Ethics, Educational Sciences, Linguistics, Law, Economy, Criminology, Health, Sports, Geography, and others. This interdisciplinary set-up offers an ideal framework to conduct Computer Sciences projects with direct benefit for the partner institutions involved as well as positive impact on the use of digital technology in public management (city administration), in companies, and in society.
Basics and Methods in Humanities and Social Science (2 ECTS)
Lecturer: Prof. Dr. Nikol Rummel
Abstract: To be well prepared for work on the intersection of Computer Science and Social Sciences / Humanities, ISI students learn fundamentals in Humanities and Social Sciences and methods to holistically assess the current problems in the field of digital transformation and IT security. Both, fundamental concepts from the respective disciplines (such as linguistics, social science, media studies and psychology) as well as up-to-date topics in the field of data protection (such as the right to privacy) will be covered. Alternating lecturers from the Humanities and Social Sciences will present topics related to digitization from the perspective of their particular discipline, in one to two sessions each. A session consists of 45 minutes of lecture and 45 minutes of work in groups.
Basket Social Sciences, Innovation, and Digital Transformation
Privacy and Public Interaction in Social Media (5 ECTS)
Lecturer: Rahim Benrazavi
Abstract: The seminar will look into perspectives of online media and elaborate on different functions of social media such as Privacy in Social Media, Media Literacy, Media and PR Effects, Social Media and Youth Protection, Copyrights, as well as other social and global issues concerning social media in a timely manner. The seminar will mainly focus on methods of improving the children and young adults’ experience of using social media.
Current Trends in Innovation Management (5 ECTS)
Lecturer: Prof. Dr. Matthias Weiß
Abstract: Organizational innovation has gained increasing attention throughout the years as organizations face environmental pressures that force them to continuously innovate. Being a multi-level phenomenon, the understanding of innovation management is crucial for successful development and implementation of the new services, products, or processes. The fundamental objective of this course is hence to explore current trends in innovation management to better explain the phenomenon of innovation in organizational settings.
The Economics of Digitalization (5 ECTS)
Lecturer: Prof. Dr. Marianne Saam
Abstract: Digitalization affects the economy in a fundamental way. It affects production, factor and consumer markets, work and distribution of opportunities and income. The lecture offers an introduction to the research on the economic consequences of digitalization. In the tutorial, students will engage with research results and political statements related to the digitalization of the economy.
Basket Computational Neuroscience (CNS)
Computational Neuroscience: Neural Dynamics (6 ECTS)
Lecturer: Prof. Dr. Gregor Schöner
Abstract: This course provides an introduction into the theoretical cognitive and functional neurosciences from a particular theoretical vantage point, the dynamical systems approach.
Deep Learning for Computer Vision (6 ECTS)
Lecturer: Jun.-Prof. Dr. Sebastian Houben
Abstract: The participants learn to understand, implement, and extend the main deep learning approaches with applications in computer vision.
Seminar Computational Cognitive Modelling (3 ECTS)
Lecturer: Prof. Dr. Sen Cheng
Abstract: To study the mind, the field of cognitive science pursues an interdisciplinary approach. One of the pillars of cognitive science is computational modeling. This seminar surveys models of perception, memory and action. Rather than focusing on the mathematical details, we discuss the motivation, application and noteworthy properties of the models, including their strengths and shortcomings.
Basket Machine Learning (ML)
Machine Learning: Evolutionary Algorithms (6 ECTS)
Lecturer: Prof. Dr. Tobias Glasmachers
Abstract: This course gives an introduction into Evolutionary Algorithms, which are randomized optimization methods. They are inspired principles of biological evolution, however, applied in a technical context for the solution of mathematical or technical optimization problems.
Machine Learning: Unsupervised Methods (6 ECTS)
Lecturer: Prof. Dr. Laurenz Wiskott
Abstract: This course covers a variety of unsupervised methods from machine learning such as principal component analysis, independent component analysis, slow feature analysis, vector quantization, clustering, and Laplacian eigenmaps. A brief discussion of reinforcement learning is also included.
Design Optimization (6 ECTS)
Lecturers: Prof. Dr. M. König, Dr. K. Lehne
Abstract: The aim of this course is both to teach the basics of mathematical optimization as well as the solution of optimization problems from the area of structural optimization.
Fundamentals of GPU Programming (4 ECTS)
Lecturer: Dr. Denis Eremin
Abstract: Students learn how to program on graphics processing units (GPUs).
Bioinformatics (BI)
Bioinformatics in Proteomics I (5 ECTS)
Lecturer: Dr. Martin Eisenacher
Abstract: Students get to know current methods of proteomics bioinformatics used for the analysis of raw data (mass spectra) and results (peptide/protein identification and quantification). In addition, students capture the algorithmic and statistical ideas underlying the methods and learn how the methods are applied in practice to real data and questions.
Big Data in Bioinformatics (5 ECTS)
Lecturers: Prof. Dr. Axel Mosig, Dr. Martin Eisenacher
Abstract: The practical course teaches the basics of programming in relation to life science applications with large amounts of data. This is done by current examples from the three subject areas: sequence analysis, image processing, and Bioinformatics of proteomics.
Bioimage Informatics (5 ECTS)
Lecturer: Prof. Dr. Axel Mosig
Abstract: The students get to know elementary and current techniques of image processing which are used for the analysis of microscopic image data. They should understand the underlying algorithmic, mathematical and statistical ideas, and learn in practice how to apply these methods to real data and questions.
Seminar Bioinformatics (3 ECTS)
Lecturer: Prof. Dr. Axel Mosig
Abstract: The learning objective is to independently deal with a topic from the field of Bioinformatics.
Non Awarded courses
RUB30. German as a Foreign Language
Abstract: Theses courses, adapted to students’ proficiency, introduce them to German as a foreign language or enhance the communicative skills of advanced students in German.