Master Curricula

This profile focuses on the measurement of human behavior using vision-based technologies (such as eye tracking, hand tracking and object pose estimation) and the computation of meaningful metrics quantifying human behavior in form of objective key performance indicators. Master’s studies include courses covering the basics of machine learning and computer vision as well as specific fields of application such as surgical training, rehabilitation or collaborative robotics. Semester project and Master thesis are usually embedded in research projects with industrial and/or clinical partners.

• Introduction to Machine Learning (FS, 8 ECTS, Prof. Krause)
• Computer Vision (HS, 4 ECTS, Prof. Pollefeys)
• Human Computer Interaction (HS, 4 ECTS, Prof. Holz)
• Image Analysis and Computer Vision (HS, 4 ECTS, Prof. Konukoglu)
• Biomedical Engineering (HS, 4 ECTS, Prof. Vörös)

• 3D Vision (FS, 5 ECTS, Prof. Pollefeys)
• Digital Humans (FS, 8 ECTS, Prof. Tang)
• Robot Dynamics (HS, 4 ECTS, Prof. Hutter)
• Physical Human Robot Interaction (HS, 4ECTS, Prof. Lambercy)
• Biomedical Imaging (HS, 4 ECTS, Prof. Kozerke)
• Rehabilitation Engineering I (FS, 4 ECTS, Prof. Riener)
• Medical Technology Innovation (HS, 4 ECTS, Prof. Herrmann)
• Stochastic Methods for Engineers and Natural Scientists (HS, 4 ECTS, Dr. Meyer-Massetti)

• Mixed Reality (HS, 5 ECTS, Prof. Bauer)
• Soccer Analytics (FS, 3 ECTS, Prof. Brandes)

This profile focuses on technology-driven product innovation, based on the intersection of new design tools and new manufacturing technologies. The Master's program includes a wide range of courses focusing on design, manufacturing, machine learning, simulation, optimization and Design of Experiment. Semester project and Master thesis are usually embedded in research projects with industrial partners.

• Computational Design I & II (HS & FS, 2 ECTS, Prof. Dillenburger)
• Design for Additive Manufacturing (HS, 4 ECTS, Prof. Meboldt)
• Metal Additive Manufacturing – Fundamentals and Process Technology (FS, 4 ECTS, Prof. Bambach)
• Metal Additive Manufacturing - Mechanical Integrity and Process Simulation (HS, 4 ECTS, Dr. Hosseini)
• Manufacturing (HS, 4 ECTS, Prof. Bambach)
• Experimental Methods for Engineers (FS, 4 ECTS, Prof. Coletti)
• Introduction to Machine Learning (FS, 8 ECTS, Prof. Krause)

• Computational Design III & IV (HS & FS, 2 ECTS, Prof. Gramazio)
• Programming with Python (FS, 3 ECTS, Dr. Fässler)
• Multiphysics Modelling and Simulation (HS, 4 ECTS, Dr. Roman)
• Case Studies in Computer Aided Engineering - Applied FEM (FS, 4 ECTS, Dr. Valtorta)
• Optimization and Machine Learning (FS, 4 ECTS, Prof. Mohr)
• Engineering Design Optimization (HS, 4 ECTS, Prof. Shea)
• Advanced CFD Methods (FS, 4 KP, Prof. Jenny)
• Applied Finite Element Analysis (HS, 4 KP, Prof. Mohr)
• Structural Optimization (FS, 4 KP, Dr. Stankovic)
• Experimental Mechanics (FS, 4 KP, Dr. Carrara)

• Skills for Creativity and Innovation (HS, 4 ECTS, Dr. Goller)
• Information Technologies in the Digital Product (FS, 4 ECTS, Dr. Zwicker)
• Sustainable Materials (HS, 4 ECTS, Dr. Deillon)
• Product Development and engineering design Shea (FS, 4 KP, Prof. Shea)

Purpose. Prepares students to drive innovation in industry: identify key uncertainties, test and iterate fast, and navigate corporate hurdles to deliver impact. Ideal for future innovation leaders, product developers, and entrepreneurs.

Hybrid Curriculum for T-profile The best innovators have both deep technical knowledge (T-vertical) AND management/leadership skills (T-horizontal).
Within this curriculum students therefor pick an additional technology vertical and take 50% of ETCS from that field. The vertical can be chosen either from the other pd|z curricula or other DMAVT master programs.
Core element of the T-horizontal is participation in the external page Exploration Lab - a 6-month program as a combined industry internship and semester project (from 2026).

What you’ll learn

• Lean & agile methods for product and business innovation.
• Rapid prototyping and testing with modern tools.
• Strategies to move innovation through complex organizations.
• Framing/attacking uncertainties with critical thinking.

• Lean De-Risking (new pd|z course, starting 2026): principles & practice of uncertainty-driven development.
• Design Thinking (PBLabs): human-centred discovery-to-prototype in teams. 
• Lean Startup Academy (MTEC, Chair of Entrepreneurship): idea validation, experiments, metrics. 
• Product Development and Engineering Design(MAVT): hands-on introduction to early phases of product development process
• Engineering Design and Material Selection (MAVT): hands-on skills for prototyping, such as CAD, 3D printing

Graduates have to option to apply to becoming an employed ETH coach within Exploration Lab after graduation. You will be responsible for team of students at one of our partner companies (industry-competitive salary). 

• Coaching Students (PBLabs) — Core coach training covering foundation, team, and 1:1 coaching skills plus a reflective session; blended learning on Moodle + hands-on workshops. Builds role clarity, feedback techniques, and tools to empower student teams. 
• Facilitating Student Workshops (PBLabs) — Design, lead, and debrief student workshops; practice full-cycle facilitation with observation and expert feedback; focuses on structure, moderation, and debrief quality. 

Pick a vertical to deepen technical expertise—either from pd|z master curricula or an approved D-MAVT MSc program:

pd|z Curricula: Human Behavior, Design for New Technologies

DMAVT MSc Programs: Process Engineering, Robotics, Systems and Control, Mirco and Nanosystems, Nuclear Engineering

• external page Exploration Lab: interdisciplinary student team explores innovation opportunities with a partner company (6 months, full-time, combined industry internship + semester project)
• Master Thesis: deep dive project with industry partner on topic identified during Exploration Lab (6 months, full-time)