Blekinge Institute of Technology
Master’s Programme in Machine Learning, Sensors and Systems (120 credits)
Karlskrona, Sweden
Master degree
DURATION
2 years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
Aug 2027
TUITION FEES
SEK 70,000 / per semester *
STUDY FORMAT
On-Campus
* EU/EEA Citizens are not required to pay fees
Key Summary
About: The Master’s programme in Machine Learning, Sensors and Systems (120 credits) trains you in intelligent systems combining electrical engineering and computer science. You'll apply AI, sensors, and control engineering across sectors. You'll learn machine learning, sensors, control engineering, systems engineering and data-driven methods to analyze, design, and build AI-enabled sensing and control solutions for energy, robotics, communication and healthcare.
Career Outcomes: Career opportunities include roles as systems engineer, AI specialist, research engineer, and sensor developer. You can work in energy systems, environmental technology, communications, autonomous vehicles, robotics, and medical technology, or continue with doctoral studies in related research fields.
The Master’s programme in Machine Learning, Sensors and Systems equips you with advanced technical expertise, focusing on intelligent systems. The programme combines subjects from electrical engineering and computer science – a combination that is becoming increasingly important as technology grows more complex and integrated.
You will develop your ability to analyse, understand, and build systems where AI, sensors, and control engineering interact – skills in high demand across sectors such as energy, robotics, communication, and healthcare.
Tomorrow’s technical solutions require expertise across multiple disciplines. This Master’s programme brings together electrical engineering and computer science – two fields that are essential for developing sustainable, smart systems in an increasingly connected world.
You will gain the skills to work with complex technical systems, where machine learning and sensors interact to create intelligent solutions in areas such as energy, communication, transport, and healthcare.
The programme provides in-depth knowledge in both data-driven and model-based technological development. You will study subjects such as:
- machine learning and AI
- signal processing
- control engineering
- mechatronics and robotics
- sensor systems
- statistics and optimisation
You will learn to combine these areas of expertise to analyse problems from different perspectives and select appropriate solutions – sometimes using advanced AI, at other times simpler model-based techniques.
During the programme, you will take part in a project course where theory meets practice. Your studies will conclude with a Master’s thesis, which can be carried out in either electrical engineering or computer science, depending on your chosen specialisation.
This is a distinctly engineering-focused programme, developed in collaboration with industry partners working in both research and application. You will gain the competence to work at the intersection of systems engineering and AI – a field with a current skills gap and rapidly growing demand.
After graduation, you may work with:
- developing sensors and intelligent systems
- optimising technical processes using AI and data-driven analysis
- working as a systems engineer, AI specialist, or research engineer
You may find employment in sectors such as:
- energy systems and environmental technology
- communication and infrastructure
- autonomous vehicles and robotics
- medical and healthcare technology
The programme also provides a solid foundation for pursuing doctoral studies.
BTH scholarship programme for prospective students
BTH scholarship programme for prospective students is available for citizens from non-EU/EEA countries who are required to pay tuition fees for a Swedish university education. Students can only apply for this scholarship before commencing a programme. Applicants to distance education at BTH are not eligible to apply for this scholarship.
The Swedish Institute Scholarship Pioneering Women in STEM for Prospective Students
The Swedish Institute Scholarship Pioneering Women in STEM is open to female citizens from eligible countries and applies to designated master’s programmes starting in the autumn semester of 2025. Eligible applicants can only apply for this scholarship before commencing the programme. Applicants must also be required to pay tuition fees for a Swedish university education.
BTH scholarship programme for current students
- Students who are already enrolled and registered in a campus programme at BTH and have at least two semesters of the nominal study time left can apply for this scholarship.
- You also have to be required to pay tuition fee for the remaining part of your programme.
- The scholarships will cover your tuition fee in part, and do not cover your living costs.
BTH will award a number of scholarships corresponding to partial reduction of the tuition fee to students with excellent academic performance during the first part of their studies at Blekinge Institute of Technology.
Our call for application will be updated on this website as of mid-October.
Other scholarship opportunities
- Swedish Institute (SI)
The Swedish Institute (SI), a government agency, promotes interest and trust in Sweden around the world. SI offers a range of scholarships for students from countries outside the EU/EEA area.
In order to get more information about the Swedish Institute scholarships, funds and grants, please visit the Swedish Institute website. These scholarships have different deadlines, so check the dates carefully.
- Study in Sweden
- Your Government or other sources in your country
General Data Protection Regulation (GDPR)
Your personal integrity is important to us at Blekinge Institute of Technology. It is therefore important to us that processing of personal information is done in a correct and safe manner in accordance with applicable laws and regulations. The university follows the general data protection regulation, more commonly known as GDPR.
Year 1 – Foundations and specialisation
The first year provides a solid foundation in the technologies used to build intelligent systems. You will take courses in:
- signals and systems
- control theory
- statistics and time series analysis
- artificial intelligence and deep learning
Depending on your interests and future goals, you will choose courses that align with a focus on either electrical engineering or computer science. For example, you may specialise in optimisation, electromagnetic field theory, or advanced machine learning.
Year 2 – Application, specialisation, and research
In the second year, the focus shifts towards practical application and research-oriented learning. Courses include topics such as:
- sensor systems
- computer vision
- robotics
- research methodology
You also have the opportunity to further specialise within your chosen field, for example through courses in radar systems (for electrical engineering) or AI system security (for computer science).
Master’s Thesis – Expertise and collaboration
The programme concludes with a Master’s thesis, giving you the opportunity to:
- specialise in a chosen subject area
- apply your knowledge in a real-world project
- collaborate with researchers or industry partners
The thesis can be part of an ongoing research project and gives you the chance to demonstrate your skills in practice – whether your goal is a career in industry or further academic research.
The study programmes at BTH are continuously monitored and developed through yearly follow-up dialogues, course evaluations after each completed course, and programme evaluations. Results from follow-ups and evaluations can lead to changes in the programmes. These changes are always communicated to the students.
Each educational programme is tied to an advisory board that discusses issues such as the quality of the programme, its development, and relevance for the labour market. In the advisory board, or a committee to the advisory board, teachers, external members, students and alumni are represented.