Program

Structure

1st Semester

Modules Artificial Intelligence, Medicine and Applications

In the first semester, students have to register for the following mandatory courses from the modules Artificial Intelligence, Medicine and Applications:

Artificial Intelligence (AI)
 Mandatory Courses
Introduction to Artificial Intelligence  5 ECTS
Machine Learning  5 ECTS
Medicine
 Mandatory Courses
Basics in Physiology  3 ECTS
Introduction to Clinics  4 ECTS
Applications
 Mandatory Courses
Computer Vision  5 ECTS
Introduction to Digital Signal Processing  3 ECTS

Module Foundation / Electives

The selection of courses from the module Foundation depends on the students' individual scientific background, from the module Electives on the students' interests.

Students may only consider courses in the selection below. Should you wish to take a course outside of the selection, please contact the study coordination and Professor Mougiakakou for an assessment of the course. 

Foundation / Electives
 Non-Mandatory Courses / Pool of Courses

Foundation
Applied Biostatics with Practicals I  4 ECTS
Applied Optimization  5 ECTS
HPC and Cloud Computing  1 ECTS
Internet of Things  5 ECTS
Introduction to Programming  2 ECTS
Linear Models and Regression I  9 ECTS
Numerical Methods  5 ECTS
Selected Chapters in Mathematics  2 ECTS

Electives
 none

2nd Semester

Modules Artificial Intelligence, Medicine and Applications

In the second semester, students have to register for the following mandatory courses from the modules Artificial Intelligence, Medicine and Applications:

Artificial Intelligence (AI)
 Mandatory Courses
Deep Learning  5 ECTS
Medicine
 Mandatory Courses
Clinical Implementations of AI  4 ECTS
Applications
 Mandatory Courses
Clinical Decision Support  3 ECTS
AI for Medical Time Series Data (replaced by Trustworthy AI in Medicine for 2025)  3 ECTS
Trustworthy AI in Medicine (2025 only)  3 ECTS

Module Foundation / Electives

The selection of courses from the module Foundation depends on the students' individual scientific background, from the module Electives on the students' interests.

Students may only consider courses in the selection below. Should you wish to take a course outside of the selection, please contact the study coordination and Professor Mougiakakou for an assessment of the course. 

Foundation / Electives

Foundations
3D Geometry Processing  5 ECTS
Applied Biostatistics II. with Practicals  4 ECTS
C++ Programming I   3 ECTS
Cryptography  5 ECTS
Distributed Algorithms (on hold)  5 ECTS
Ethical and Legal Issues  3 ECTS
Graph-based Pattern Recognition  5 ECTS
Introduction to Medical Statistics  3 ECTS
Seminar Applied Optimisation   5 ECTS
Seminar Machine Learning and Artificial Intelligence 5 ECTS

Electives
Advanced Networking and Future Internet  5 ECTS
Algorithms, Probability and Information  5 ECTS
Biomedical Sensors  3 ECTS
Biomedical Signal Processing and Analysis  3 ECTS
Clinical Epidemiology and Health Technology Assessment  2 ECTS
Computer-Assisted Surgery  3 ECTS
Databases (in German)  5 ECTS
Finite Element Analysis I  3 ECTS
Fundamentals of Quality Management and Regulatory Affairs  4 ECTS
Genomics of Microorganisms  1.5 ECTS
Image-Guided Therapy Project (on hold)  3 ECTS
Introduction Image Analysis  3 ECTS
Introduction to Precision Medicine  3 ECTS
Medical Robotics   3 ECTS
Microsystems Engineering  3 ECTS
Proteomics & Metabolomics (lecture and practicals)  5 ECTS
Regenerative Dentistry for Biomedical Engineering  2 ECTS
Rehabilitation Technology  3 ECTS

3rd Semester

Modules Artificial Intelligence, Medicine and Applications

In the third semester, students have to register for the following mandatory courses from the modules Artificial Intelligence, Medicine and Applications:

Artificial Intelligence (AI)
 Mandatory Courses
Reinforcement Learning   5 ECTS
Medicine
 Mandatory Courses
Clinical Implementations of AI II  4 ECTS
Omics for Non-Biologists  3 ECTS
Applications
 Mandatory Courses
Medical Image Analysis  3 ECTS
From NLP to LLMs  3 ECTS

Module Foundation / Electives

The selection of courses from the module Foundation depends on the students' individual scientific background, from the module Electives on the students' interests.

Students may only consider courses in the selection below. Should you wish to take a course outside of the selection, please contact the study coordination and Professor Mougiakakou for an assessment of the course. 

Foundation / Electives

Foundations
Applied Optimisation  5 ECTS
Computer Graphics  5 ECTS
HPC and Cloud Computing  1 ECTS
Internet of Things  5 ECTS
Linear Models and Regression I   9 ECTS
Medical Informatics  3 ECTS
Seminar Machine Learning and Artificial Intelligence  5 ECTS


Electives
Cardiovascular Technology  3 ECTS
Computer Graphics & Geometry Processing  5 ECTS
Data Driven Diabetes Management  3 ECTS
Digital Sustainability  1 ECTS
Innovation Management  2 ECTS
Intelligent Implants and Surgical Instruments  3 ECTS
Medical Image Analysis Lab  4 ECTS
Molecular Biology and Genetics for Non-Biologists (Lecture)  3 ECTS
Neurotechnology   3 ECTS
Ophtalmic Technologies  3 ECTS
Seminar in Cryptography and Data Security  5 ECTS


4th Semester

The 4th semester is reserved for the master's thesis. You can find more information in the following link.

Study & Work

Most of our students study full-time and work at the same time. We support them and organize mandatory courses on three days of the week only.

Students who work may officially request to extend their studies to six semesters.

Interested in finding a job in the industry? Then the University of Bern is the place to be! There are around 280 medical technology manufacturers and suppliers in the canton of Bern and the sector is constantly growing, with the number of jobs in medical technology rising. (Source: Swiss Medtech (Network) Bern Economic Development Agency)

Our 12 different research groups at the ARTORG Center offer part-time jobs to excellent students. If you are interested please contact us after you have been accepted into our master's program.

 

 

Preparation Week

Do you want to brush up on your maths before the start of the program?

The preparation week provides an opportunity for students to work on their skills and be prepared for the master's program Artificial Intelligence in Medicine at the University of Bern.

By combining theoretical lectures on linear algebra, optimization and probability with a rich array of practical exercises in Python, MSc AIM's fall session will successfully prepare you for the new and exciting challenges!

2025 preparation week:

  • 8th September: Linear Algebra (class 9h-12h, practical 14h-17h)
  • 9th September: Linear Algebra (class 9h-12h, practical 14h-17h)
  • 10th September: Probability (class 9h-12h, practical 14h-17h)
  • 11th September: Optimisation (class 9h-12h, practical 14h-17h)
  • 12th September: 9:30-11h Welcome Event followed by "Cafe und Gipfeli"

We are still confirming the location of the preparation week within the University of Bern as it will depend on the number of sign ups. Once we have booked a room, we will update the location in KSL and post it on here. 

Alongside the AIM preparation week, the university organises the "Tag des Studienbeginns" on the 12th of September. The day includes a few talks from the faculty of medicine and a freshers fair with student clubs of the university. More information can be found on the university website.

Click here to view the week in KSL

Registration to preparation week 2025 and welcome event

Arrangements

Students with disabilities or chronic illnesses have a right to Access Arrangements. 

Please refer to the university page for the procedure to follow to obtain the arrangement required.