Data-Centric Engineering LUT University

Overview

To develop innovative solutions to the world's most challenging problems, it is increasingly important to properly understand data and modern information processing methods.

During your studies, you will learn about artificial intelligence and machine learning and how mathematics and statistics form their basis. This will enable you to understand data and modern modelling and analysis methods, such as deep neural networks, profoundly and apply them to problems with societal impact. You will specialise in either Applied Mathematics, or Computer Vision and Pattern Recognition.

The Data-Centric Engineering programme from LUT University is designed for students with a BSc degree in mathematics, applied mathematics, statistics, computer science, artificial intelligence, or the like. 

In this programme, you will have extensive possibilities for international experiences, such as Erasmus exchange and double degree programmes with partner universities. In double degree programmes, you will get MSc degrees from both LUT and its partner university.

Career prospects

Data-centric engineering provides a solid stepping-stone to a career in academia, government, industry, or finance, as well as entrepreneurial skills for establishing a start-up company.

The skills and competencies gained in the programme prepare you for continual learning and for the ongoing transition from software-intensive to data-intensive engineering work.

Practical examples of our graduates' careers include various positions in artificial intelligence companies; for example, developing computer vision and virtual reality, enhancing the capability of medical imaging in medical engineering companies, working on modelling and simulation in industry R&D, different positions at universities and research institutes at all career levels from junior researchers to professors.

Lucrative start-up companies founded by our alumni contribute to sawmill industry digitalisation, computer vision for industry and environmental monitoring.