Efficient and sustainable technologies

As soon as a technical system has an actuator or a process has an adjustable parameter, as an automation engineer you ask yourself how the system or process can be made more efficient and intelligent, for example to save resources and energy and therefore costs. This should not only benefit people, but also the environment.

Fields of application

Automation technology covers the following areas

• Robotics: industrial robotics (e.g. robot arms), autonomous driving, other mobile robotics (e.g. fpor transportation), medical robotics
• Control of renewable energy systems: wind and solar power plants
• Industry & plant engineering: process industry optimization (chemical and pharmaceutical industry, oil and gas extraction, metal and paper industry), plant automation, logistics
• Aerospace control systems: aircrafts, satellites, rockets

Focus in teaching

The Bachelor's degree teaches the basics of control engineering, which provides you with a universal set of tools to control any processes and systems, i.e. to control them efficiently and automatically. However, the processes and technical systems must be understood before they can be controlled, which is taught under the heading of modeling and identification. In various internships and project seminars, you will get to know different technical systems, e.g. technical fluid systems, helicopters, airplanes, container cranes, autonomous cars and many more, and then apply controls and automation concepts you have learned to them. In the Master's program, you will learn advanced and modern control methods. You will implement concepts from optimization and artificial intelligence. Here you can flexibly set a wide variety of focal points in your studies: For example, in methods of machine learning, concepts of autonomous driving, fundamentals of image processing or the control of cyber-physical systems.

Occupational fields

The job prospects of automation engineers are as diverse and promising as their fields of application. Whether research, development, planning, organization or sales. Automation engineers are needed and valued everywhere. Do you want to build the autonomous car of tomorrow that can withstand even the most adverse weather conditions? Do you want to design modern hydrogen plants? …make airplanes fly autonomously? …land rockets safely? … develop bioreactors? … ship medicine and vaccines faster? … Make a chemical process more environmentally friendly? The expertise of automation engineers is in demand everywhere. And that's why companies like ESA, Bosch, Evonik, Zeiss, Merck, ABB, Continental, Sirona, Kuka, Porsche, Airbus and many more are always looking for you.

Shaping the digital world

The Data Technology specialization in the Bachelor's/Master's degree program in Electrical Engineering at TU Darmstadt focuses on the theory and application of data processing systems, networks and technologies. It covers aspects of information transmission, data analysis, signal processing, software engineering, embedded system development and circuit technology.

Fields of application

Knowledge from the data technology specialization is in demand in a variety of areas, including telecommunications, Internet of Things (IoT), Industry 4.0, medical technology, autonomous driving, energy transition, artificial intelligence and robotics. Graduates are able to design, implement and optimize complex systems that can process and transmit large amounts of data.

Focus in teaching

The course content covers a wide range of topics, including digital signal processing, coding theory, wireless communication, networks, computer architecture, embedded systems, software engineering, embedded system development, machine learning and big data analysis. Practical exercises, lab work and project work are integral parts of the program to give students hands-on experience and prepare them for real-world challenges.

Occupational fields

Graduates with a specialization in data engineering will find employment opportunities in various industries, including telecommunications companies, software development, IT consulting, the automotive industry, medical technology companies, research institutes and companies in the field of energy transition. Possible job titles include data engineer, system architect, network administrator, signal processing specialist, IoT developer, software and hardware developer for embedded systems and artificial intelligence researcher. In the energy transition, they play a key role in the development and implementation of technologies for the integration of renewable energies, energy efficiency and smart grids.

Model. Solve. Create.

CMEE is concerned with the physical and data-driven modeling, simulation and optimization of electrotechnical phenomena, devices and, where applicable, processes.

Fields of application

Like mathematics or computer science, CMEE is a cross-sectional discipline that primarily teaches methodological skills. These skills are used in the computer-aided optimization of electrical machines or high-voltage arresters as well as in the simulation of biomolecular circuit models in synthetic biology. Electricity price models are also based on probabilistic models and are calculated using numerical methods. In order to do justice to this flexibility in application, the CMEE curriculum provides for a specialization in at least one field of application.

Focus of teaching

The course content covers the fundamentals of scientific computing, e.g. discretization methods for differential equations such as Maxwell's equations, but also data-driven approaches such as machine learning in the context of electrical engineering issues. In these disciplines, TU Darmstadt and the lecturers of the degree program have an excellent track record in research and teaching, e.g. visible through the cross-cutting topic of computational engineering, which was anchored at TU Darmstadt as part of the Excellence Initiative, or through participation in the Hessian Center for Artificial Intelligence.

Occupational fields

Graduates of the CMEE specialization often work as simulation or calculation engineers and carry out virtual computer experiments in the electrical industry using simulation software. However, they also work as software developers who develop and implement complex numerical algorithms, in project management, e.g. in medical technology, as consultants for digitization issues or as founders of IT companies.

Solutions for the energy transition

Electrical power engineering deals with the comprehensive design, generation, distribution and efficient use of electrical energy.

Fields of application

Electrical power engineering is crucial for all areas of life, as electrical energy is the basic requirement of modern society today. Engineers in power engineering are therefore more in demand than ever. The challenge is not only to ensure a secure energy supply, but also to make it economically efficient and environmentally friendly. You play an active role in shaping a sustainable energy supply.

Focus in teaching

Your course content covers all facets from energy generation to consumption. In order to secure the central role of energy supply for technological progress in the future, our students learn the basic technical knowledge required for the generation, transmission and use of electrical energy. However, your courses not only focus on technical aspects, but also place particular emphasis on interdisciplinarity and understanding the technical interrelationships of a wide range of systems, including the use of generation plants and storage facilities by means of optimization, probabilistic models and machine learning.

Occupational fields

The professional fields for our graduates range from energy supply companies, manufacturing industry, transport companies and public institutions to traditional engineering offices. As a qualified engineer, you can work in a variety of areas: from product development and plant planning to as a specialist with personnel responsibility. With your degree from TU Darmstadt, your specialization and interdisciplinarity will make you stand out. In the context of the energy transition, there are many exciting challenges that you can contribute to.

Networking people, devices and industry

The Communication Technology and Sensor Systems specialization deals with new technologies across the entire spectrum from theory, hardware and software to complete systems and networks in order to make communication and sensor technology more efficient. KTS topics are drivers of innovation in many industries.

Fields of application

The specialization is very broadly based, resulting in numerous fields of application with numerous job profiles. Some examples:

• Biomedicine
• Safety engineering
• Semiconductor technology
• Localization and navigation
• Smart and resilient infrastructure
• Machine learning
• Spectroscopy and optical sensor technology
• Microwave and ultra-high frequency technology up to terahertz waves
• Mobile radio and satellite technology

Presentation of the focus areas in teaching

The course content reflects the wide range of the specialization, there is something for everyone. Starting with the theoretical basics of signal processing, communication and information theory, the course quickly moves on to application-oriented topics such as antenna technology, optical and high-frequency components and systems and synthetic biology.

Occupational fields

With a degree with a specialization in KTS in your pocket, you will be spoilt for choice when it comes to your career. Whether you want to work outside your field in finance or as a data technician, in basic research or in a very applied field in industry: many doors are open to you. You are highly qualified for current professions in the information age.

Electrical engineering hardware systems

Today, sensors, actuators and electronics are not separate functional blocks, but are increasingly merging both spatially and functionally (integration).

Fields of application

From complete systems to micro- and nanoelectronics: In the field of sensors, actuators and electronics (SAE), we work with dimensions of several orders of magnitude. Building hardware is just as much a part of our remit as carrying out measurements and calculations. Miniaturized sensors and actuators have become indispensable in automotive, automation and medical technology, whether in airbags, positioning systems or surgical and diagnostic devices.

Focus in teaching

Without a sound knowledge of sensor, material and component properties and physical readout/amplification or signal processing using analog and digital electronics, the design of a sensor system is simply impossible. Our teaching therefore focuses on the theory and application of sensors, actuators and electronics in various areas. We impart knowledge about the design and implementation processes of SAE systems as well as the integration of micro and nano systems. We also offer insights into modern technologies such as electronics, new materials and processes (CAD, 3D printing) as well as innovative design tools and modeling methods.

Occupational fields

SAE makes you a sought-after top specialist for development as well as research. Our students are prepared for a wide range of career paths. You can work in areas such as autonomous driving and electromobility, robotics and artificial intelligence, Industry 4.0 and Internet-of-Things, consumer electronics and communication, medical and biomedical engineering, as well as human-machine interaction and automation technology. Thanks to your in-depth training, you will be able to develop and implement innovative solutions in these forward-looking industries.

Foundations for mobility, robotics and networking

In today's world, devices and applications are increasingly networked and continuously exchange measurement data and information via wireless interfaces in order to coordinate their behavior with regard to common overarching goals. Aspects such as the optimization of communication effort, the coordinated management of available computing, storage and battery resources in the network as well as the efficiency of distributed signal processing, learning and control algorithms play a major role here.

Fields of application

Distributed autonomous systems (VAS), often referred to as multi-agent systems, are used in numerous areas. In logistics, autonomous agents manage stock levels, optimize transport routes and reduce delivery times. In traffic management, autonomous vehicles jointly coordinate the flow of traffic in cities, prevent traffic jams and optimize routes. In intelligent energy systems, decentralized agents optimize energy distribution, monitor energy consumption and integrate renewable energy sources. In smart factories, robotic agents automate and optimize production processes, including assembly, inspection and maintenance. In trading systems, decentralized agents carry out market analyses, develop trading strategies and execute transactions. In telecommunications, agents optimize resource usage, monitor the network, detect anomalies and respond to security threats. In healthcare, agents collect and analyze medical data, support diagnosis and make therapy suggestions. In online recommendation systems, agents personalize users' online shopping experiences, analyse their behaviour, make product recommendations and broker sales. In disaster control, agents coordinate rescue operations, monitor endangered areas and support decision-making in crisis situations. In artificial intelligence, VAS solve problems together and learn from each other while ensuring the security and privacy of local databases.

Focus in teaching

Since the middle of the last century, various fundamental sub-disciplines of electrical engineering, such as communication theory, signal theory, control engineering, information theory, computer science and machine learning theory, have developed independently of each other. With increasing networking and the associated opportunities and challenges in connection with distributed autonomous systems, we are observing a reversal of this development. Together with mathematical optimization and graph theory, these fundamental areas of electrical engineering form the focus of teaching in the VAS specialization.

Occupational fields

Students in the VAS specialization receive a comprehensive education in the above-mentioned fundamental areas of electrical engineering. As part of their scientific studies, they are systematically prepared to make important contributions to networked and distributed systems in a wide range of application areas in research and development both at universities and research institutes and in industry.