A Specialization is a set of courses allowing students to deepen their knowledge of a specific aspect of their main discipline. It therefore offers them the opportunity to develop expertise in a particular area of their Master’s program.
A specialization corresponds to 30 ECTS that must be acquired during the Master’s studies.
Students may validate a Specialization or a Minor, but not both. Specializations or Minors will be listed in the Diploma Supplement.
Validation of a Specialization is optional and requires at least 30 ECTS credits with the same label (B, J, K, L) from “Core courses Engineering and Computation” and “Options”.
As part of those, it is encouraged to develop practical skills by taking a 8 ECTS Lab Immersion in the specific area.
You can only enroll in one Specialization or Minor (30 ETC within 45 ECTS optional courses).
You have until the end of the first semester (MA1) to choose a Specialization or a Minor and validate the Academic Registration Form (FRAC): http://is-academia.epfl.ch/page-6244-en.html.
You need to indicate your Specialization or Minor when you validate the academic registration form FRAC (before the start of the second semester).
Every course can only be validated once, either in Group 1 “Core courses Engineering and Computation” or in Group 2 “Options”. If you want course(s) from Group 1 to be validated within your Specialization, you have to contact the section who will move the course(s) in Group 2.
If you reach 12 credits in Group 1 “Core courses Engineering and Computation”, the additional credit won’t count in the Group 2 “Options”. You may exceed 45 credits in the “Options”. However, once you have validated all Groups in the Master cycle (90 ECTS), you will be enrolled into the Master project (30 ECTS).
Bachelor’s courses listed in a specialization that have already been validated for the Bachelor’s degree cannot be taken again for the Master’s degree and will not count towards the specialization.
The Specialization Biomedical Engineering includes topics at the interface between engineering, biology and medicine and focuses on the development of novel tools for diagnosis, prevention and treatment of human disease.
This Specialization covers disciplines such as, regenerative medicine, stem cell engineering, tissue engineering, biomaterials, medical instrumentation or image processing.
Students who choose this specialization are strongly advised to take Biomaterials (BIOENG-442), Stem cell biology and technology (BIO-447) and Tissue engineering (BIOENG-449)
Responsible: Prof. Carlotta Guiducci
The Specialization Molecular Health trains next generation life science engineers to master engineering technologies applied to biological mechanisms in human health and disease.
This Specialization completes the core LSE training as students acquire a deep knowledge and contemporary skills in disciplines such as cancer biology, immunology, infection biology, single cell genomics, bioinformatics, drug discovery, epigenetics or molecular endocrinology.
The Specialization Biological Data Science trains next generation life and data scientists to tackle today and tomorrow’s computational and big data challenges in contemporary life and biomedical sciences.
Biological Data Science is an emerging discipline that leverages computational and quantitative approaches to bring new solutions to unsolved life sciences challenges. Extracting relevant biological insights from current data fluxes requires the convergence of concepts and methods from computer science, mathematics, physics and bioengineering. This Specialization introduces a palette of approaches ranging from mathematical modeling to statistical inference and deep learning, while preparing the student to address biomedically relevant questions.
Responsible: Prof. Anne-Florence Bitbol
The Specialization in Neuroscience trains future experts in the fields of fundamental and computational neuroscience. The specialization covers topics within molecular, cellular, physiological and behavioral neurobiology in addition to mathematical and computational neuronal modeling. The specialization aims to introduce the synthesis of experimental and computational approaches that can be applied to understand healthy brain function, alleviate neuronal dysfunction or identify new and innovative therapeutic strategies.
Responsible: Prof. Brian McCabe