Automation and Robotics

TU Dortmund University · Dortmund, Germany

Level: Master's
Award: Master of Science
Language: English
Duration: 4 semesters
Study mode: Full-time
Campus: Dortmund
Apply by: Register by 15 January 2027 + 1 more
Starts: Winter and summer semester

TU Dortmund University does not publish a fee for this programme on its own. Its published rate for master's programmes is €0 – €1,940 a year for international students.

Entry requirements and how to apply

Entry requirements: It is compulsory to show mathematical proficiency and substantial knowledge in computer systems to gain admission in the course. With reference to our examination order (§3), these items are checked only by the amount of classes in the relevant directions in your BSc curriculum. Additional experience (whether from non-academic courses or from work experience) will be disregarded for formal reasons.
English language requirement: C1 required, please provide an official language certificate, e.g.: PTE Academic: 76 TOEFL iBT (since 2026): 5 Reading: 5 Listening: 5 Speaking: 5 Writing: 5 TOEFL iBT (before 2026): 95 Reading: 24 Listening: 22 Speaking: 25 Writing: 24 IELTS Academic: 7 Cambridge English Qualifications: C1 Advanced
German language requirement: No minimum language level required
Application period: The following is valid for applicants from: non-EU countries For the summer semester: 1 November - 15 January The following is valid for applicants from: non-EU countries For the winter semester: 1 January - 15 May
Apply through: Please apply via uni-assist .

About this programme

The programme offers three main areas of specialisation: Robotics: the design, modelling, control, and operation of robotic systems, including, for example, industrial, mobile, medical, collaborative, and autonomous applications Process Automation: the modelling, monitoring, optimisation, and control of complex technical, chemical, and biochemical processes Machine Learning: data-driven methods for analysing data and developing intelligent systems, including for example regression, neural networks, deep learning, transformers, reinforcement learning, computer vision, and natural language processing Students acquire a solid foundation in mathematics, control theory, robotics, data science, and scientific programming. As they progress through the programme, they can increasingly tailor their studies to their individual interests through elective courses, project work, and the Master’s thesis. Students are free to select electives from the current course catalogue. Their chosen electives determine their major field of study: Robotics, Process Automation, or Machine Learning. There is no need to select a specialisation at the beginning of the programme; students develop their individual profile as they progress through their studies. The broad range of electives enables students to explore topics such as advanced control, autonomous and mobile systems, computer vision, intelligent and data-driven methods, communication technologies, and energy-related applications. The elective c