Shape the Future of Biomedical Innovation
- Program Overview
The M1 program is designed to strengthen and broaden students’ skills in engineering, digital sciences, and Biomedical disciplines, addressing contemporary health challenges.
This one-year curriculum provides essential fundamental and practical knowledge, equipping students with an interdisciplinary background before they choose a specialized track in the second year (M2).
Semester 1
Integration, Core Science Curriculum and Adaptive Core Curriculum (30 ECTS)
The first semester (September to January) starts with an integration week. Thereafter, courses are held on a weekly basis. Students engage in a Core Science Curriculum and an Adaptative Core Curriculum totaling 30 ECTS credits (European Credit Transfer Scale).
The integration week aims at orienting students and preparing them for their academic journey. This week includes:
- The General Kickoff Meeting: Provides a comprehensive overview of the Master’s program, including structure, objectives, and expectations.
- The Individual Meeting with Academic Tutor: Each student meets with their assigned academic tutor, who is one of the M1 executive team members, to discuss their academic goals and receive personalized guidance.
- Three Integration Days: These days feature activities such as team-building exercises, student organization introductions, an outdoor walking rally, skills workshops, pitch workshops, and mock interviews.
The Core science curriculum is a compulsory common core (9 ECTS).
It encompasses two modules:
- Scientific Communication
- Open your Mind Seminars
- Medicine and Science
- Culture and Languages
- Introduction to Digital Health
To accommodate the diverse academic backgrounds of M1 students, courses are offered at both basic and advanced levels, allowing each student to address any skill gaps while advancing their knowledge in various scientific disciplines. Students follow a personalized curriculum comprising a minimum of seven courses (3 ECTS each) from the 17 options available, totaling 21 ECTS credits. This flexible structure ensures a challenging and enriching learning experience tailored to each student’s academic level and interests. All course selections require approval from the academic tutor to ensure alignment with each student’s academic and professional objectives.
Elective courses
- M1
This course aims to equip master’s students in biomedical engineering with essential skills for conducting rigorous scientific research and generating both applied and fundamental knowledge.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
- M1
This course aims to equip master’s students in biomedical engineering with essential skills for conducting rigorous scientific research and generating both applied and fundamental knowledge. Research methodology encompasses a broad array of professional practices applicable across settings, from academic institutions to corporate research environments.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
To support students from varied academic backgrounds, we offer suggested course combinations for specific fields: Engineering, Biology, and Digital Health. Each combination includes compulsory courses and a selection of electives to help students deepen expertise and address any foundational gaps.
Course Combination for Engineers
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Course Combination for Biologists
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Course Combination for Digital Health
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Semester 2
This semester (January to June) includes specialized courses aligned with the student’s intended track in the second year (M2).
Developing Complementary and Experimental Skills (30 ECTS)
Courses for NeuroTech, BIM, BioMECH, and MCB tracks
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Courses for the Digital Health track
Resume
- What are the prerequisites?
An innate curiosity and thirst for science. A solid background in statistics and mathematics is required to join the advanced group on machine learning.
Successful completion of the first year of the BME-Paris Master’s program (totaling 60 ECTS) is required to progress to the second year (M2).
- FACULTY
- Testimonials
Testimonials
faq
What is the focus of the Molecular & Cellular Biotherapies Program?
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Is this program a Master’s first year (M1) or second year (M2)?
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What academic background is required to apply?
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What are the main scientific fields covered in the curriculum?
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Does the program include laboratory or hands-on training?
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How is the program structured across the academic year?
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What is the duration of the internship in Semester 4?
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Where does the internship take place?
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