Engineering

European Project semester - 30 ECTS

The European Project (EPS) semester offers engineering students to take part a real-life, multidiciplinary project where they are challenged to solve a problem for a company or connected to one of our ongoing research projects. During the semester, the participating students will be divided into groups of 3-6 students with different engineering backgrounds. EPS is open to all engineering students in their 3rd, 4th or 5th year. The EPS is currently offered by 22 universities in 13 countries across Europe.

• European Project Semester: Interdisciplinary Engineering Project 20 ECTS
• Project Management, 5 ECTS
• Introduction to Sustainable Development from an Engineering Perspective, 3 ECTS
• Swedish Language and Culture, 2 ECTS

Business & Engineering - Bachelors level

This course packages focuses on technical aspects of business administration, for example logistics and production planning. The course package welcomes students with a background in engineering or business administration. 

Period 1

• Supply Chain Management (pdf), 7.5 ECTS
• Resource Recovery I (pdf) 7.5 ECTS

Period 2

• Demand Chain Management, 7.5 ECTS syllabus to come 
• Artificial Intelligence for Business administration 7.5 ECTS
  

Mechanical engineering project - Bachelor's level

This course package focuses around a construction project where groups of students will develop a mechatronic product prototype according to given instructions. The project will include use of AI and automation. The course package is suitable for engineering students that have completed 2 years or more  of study at the start of the exchange and have previous knowledge in Mechatronics and programming in Python.  

• Construction project 15 ECTS 
• Machine Learning and Neural Networks, 7.5 ECTS
• Resource Recovery I (pdf) 7.5 ECTS

Resource Recovery - Masters level

These courses are given within the first year of our Masters programmes in Resource Recovery. The courses are open for student with a minimum of 180 ECTS in all fields of engineering.

• Resource Recovery I (pdf) 7.5 ECTS
• Theory of Science and Research Methodology (pdf)5 ECTS
• Life Cycle Assessment (pdf) 5 ECTS
• Resource Recovery II (pdf) 7.5 ECTS 
• Circular Economy (pdf) 5 ECTS

This is the second semester of the 2025-2026 academic calendar. All new exchange students should attend the Orientation Days prior to the start of the semester.

During the spring semester we offer 5 different course packages at masters level. It is not possible to mix courses from different course packages.

Resource Recovery - Masters level
Sustainable Energy Processes

Requirements: 180 ECTS in engineering including knowledge in Thermodynamics.

• Heat Transfer in Thermal Applications (pdf)7.5 ECTS
• Thermal Energy Recovery (pdf) 7.5 ECTS
• Process design - Energy Carrier Production (pdf)  15 ECTS

Biotechnology and Bioeconomy

Requirements: 180 ECTS in engineering including knowledge in Chemistry.

• Microbiology and its industrial applications (pdf) 7.5 ECTS
• Biotechnology Processes and Applications (pdf)7.5 ECTS
• Bioprocess Design (pdf) 15 ECTS

Polymer Materials for the Circular Economy

Requirements: 180 ECTS in engineering

• Polymer Technology (pdf)  7.5 ECTS
• Polymers and Textile in Composites (pdf)7.5 ECTS
• Experimental Methods for Polymers and Textiles (pdf)7.5 ECTS
• Polymeric and Textile Materials and the Environment (pdf)7.5 ECTS

Sustainable Civil Engineering

Requirements: 180 ECTS in engineering including 60 ECTS in Civil engineering

• The Building as a System, 7.5 credits
• AI in industrial engineering, 7.5 credits
  
  • This course provides an introduction to the use of machine learning and neural networks in technical applications and industrial engineering and management. It covers, for example, basic concepts in computer science and provides an introduction to programming in Python and to the fundamentals of machine learning. In the practical exercises, Python is used with examples of machine learning in technical applications. This also includes the training and evaluation of classification and regression models.
• Mathematical Tools for Optimization and Data Processing, 7.5 credits
  • This course provides an introduction to mathematical tools used in optimization, machine learning, and data processing. It covers optimization methods, including gradient-based techniques and Lagrange multipliers, with examples from machine learning. It also addresses multi-criteria analysis to handle complex optimization problems. Within data processing, methods for image analysis are studied, as well as techniques for pattern recognition and data dimensionality reduction.
• Concrete Technology and Recycling, 7.5 credits

Project work courses can in some cases be offered to exchange students at the master level. Students will work together together with a research group in our ongoing research project. Admission are based on the availability of supervisors and of the projects relevance to ongoing research as well as the students’ previous experience. If you are interested in doing a project work course, contact the International Office at internationalstudent@hb.se

Please note that the processing time for project work courses are longer and we therefor need your application well in advance of nomination deadlines (15 of April for the Autumn semester and 15 of October for the Spring semester).