Robotics

Robotics consists of three study modules: robotics, digitalisation, and business studies. You will gain good analytical skills and wide expertise in key technologies that drive smart energy systems (such as battery energy storages, microgrids, big data analytics, artificial intelligence, 5G, hybrid AC/DC systems with power electronics), along with an understanding of future markets and business models.

After completing the degree, you will be able to:

• analyse and assess the effect of green energy transition, digitalisation and new technologies on future smart energy solutions and their sustainable production/materials circulation
• plan, research and develop new intelligent approaches to produce sustainable solutions for the future smart grids and energy systems by using a variety of computing devices
• understand the role of new technologies and components (sensors, machine learning and vision, energy storages, advanced ICT solutions), energy storages, sector-coupling, new market and business models on green energy transition
• lead and manage different new solutions development, planning and research projects as well as use existing sources of information critically and produce new knowledge in multidisciplinary field of future intelligent energy systems and smart manufacturing

Moreover, this degree provides eligibility for doctoral studies in automation engineering, communications engineering, electrical and computing engineering, or related technical fields.

These studies are arranged in the cities of Vaasa and Pori.

The major in Robotics is a part of the master’s programme in Smart Energy. The duration of studies is 2 years (120 ECTS credits).

This brand-new major will consist of 35 ECTS credits in Robotics, encompassing essential courses like Embedded C Programming, Intelligent Robotics, Applied Signal Processing, and Digital Image Processing. Additionally, you can tailor your learning experience by selecting from a range of specialised courses, such as Machine Learning, Applied Machine Learning, Machine Learning for Computer Vision, Embedded System Architecture and Design, and SoC-FPGA.

Having previous studies in subjects like electrical engineering, energy technology, automation technology, telecommunications engineering, or a similar engineering field will set you up for success. Please note that a business degree is not considered appropriate unless it includes a sufficient amount of relevant studies in technology (55%). Check out the detailed eligibility criteria for this programme in joint and rolling admission for further guidance.