Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

Search result: Catalogue data in Autumn Semester 2016

Mechanical Engineering Master Information
Core Courses
551-0319-00LCellular Biochemistry (Part I) Information W3 credits2VU. Kutay, R. I. Enchev, B. Kornmann, M. Peter, I. Zemp, further lecturers
AbstractConcepts and molecular mechanisms underlying the biochemistry of the cell, providing advanced insights into structure, function and regulation of individual cell components. Particular emphasis will be put on the spatial and temporal integration of different molecules and signaling pathways into global cellular processes such as intracellular transport, cell division & growth, and cell migration.
ObjectiveThe full-year course (551-0319-00 & 551-0320-00) focuses on the molecular mechanisms and concepts underlying the biochemistry of cellular physiology, investigating how these processes are integrated to carry out highly coordinated cellular functions. The molecular characterisation of complex cellular functions requires a combination of approaches such as biochemistry, but also cell biology and genetics. This course is therefore the occasion to discuss these techniques and their integration in modern cellular biochemistry.
The students will be able to describe the structural and functional details of individual cell components, and the spatial and temporal regulation of their interactions. In particular, they will learn to explain the integration of different molecules and signaling pathways into complex and highly dynamic cellular processes such as intracellular transport, cytoskeletal rearrangements, cell motility, cell division and cell growth. In addition, they will be able to illustrate the relevance of particular signaling pathways for cellular pathologies such as cancer.
ContentStructural and functional details of individual cell components, regulation of their interactions, and various aspects of the regulation and compartmentalisation of biochemical processes.
Topics include: biophysical and electrical properties of membranes; viral membranes; structural and functional insights into intracellular transport and targeting; vesicular trafficking and phagocytosis; post-transcriptional regulation of gene expression.
Lecture notesScripts and additional material will be provided during the semester. Please contact Dr. Alicia Smith for assistance with the learning materials. (
LiteratureRecommended supplementary literature (review articles and selected primary literature) will be provided during the course.
Prerequisites / NoticeTo attend this course the students must have a solid basic knowledge in chemistry, biochemistry and general biology. The course will be taught in English.
Design, Computation, Product Development & Manufacturing
151-0104-00LUncertainty Quantification for Engineering & Life Sciences Restricted registration - show details
Does not take place this semester.
Number of participants limited to 60.
W4 credits3GP. Koumoutsakos
AbstractQuantification of uncertainties in computational models pertaining to applications in engineering and life sciences. Exploitation of massively available data to develop computational models with quantifiable predictive capabilities. Applications of Uncertainty Quantification and Propagation to problems in mechanics, control, systems and cell biology.
ObjectiveThe course will teach fundamental concept of Uncertainty Quantification and Propagation (UQ+P) for computational models of systems in Engineering and Life Sciences. Emphasis will be placed on practical and computational aspects of UQ+P including the implementation of relevant algorithms in multicore architectures.
ContentTopics that will be covered include: Uncertainty quantification under
parametric and non-parametric modelling uncertainty, Bayesian inference with model class assessment, Markov Chain Monte Carlo simulation, prior and posterior reliability analysis.
Lecture notesThe class will be largely based on the book: Data Analysis: A Bayesian Tutorial by Devinderjit Sivia as well as on class notes and related literature that will be distributed in class.
Literature1. Data Analysis: A Bayesian Tutorial by Devinderjit Sivia
2. Probability Theory: The Logic of Science by E. T. Jaynes
3. Class Notes
Prerequisites / NoticeFundamentals of Probability, Fundamentals of Computational Modeling
151-0735-00LDynamic Behavior of Materials and Structures
Does not take place this semester.
W4 credits2V + 2UD. Mohr
AbstractLectures and computer labs concerned with the modeling of the deformation response and failure of engineering materials (metals, polymers and composites) subject to extreme loadings during manufacturing, crash, impact and blast events.
ObjectiveStudents will learn to apply, understand and develop computational models of a large spectrum of engineering materials to predict their dynamic deformation response and failure in finite element simulations. Students will become familiar with important dynamic testing techniques to identify material model parameters from experiments. The ultimate goal is to provide the students with the knowledge and skills required to engineer modern multi-material solutions for high performance structures in automotive, aerospace and navel engineering.
ContentTopics include viscoelasticity, temperature and rate dependent plasticity, dynamic brittle and ductile fracture; impulse transfer, impact and wave propagation in solids; computational aspects of material model implementation into hydrocodes; simulation of dynamic failure of structures;
Lecture notesSlides of the lectures, relevant journal papers and users manuals will be provided.
LiteratureVarious books will be recommended covering the topics discussed in class
Prerequisites / NoticeCourse in continuum mechanics (mandatory), finite element method (recommended)
151-3205-00LExperimental Ergonomics Restricted registration - show details
Number of participants limited to 15.
W4 credits2V + 2AJ. Held
AbstractYou will learn how to apply the scientific discipline of ergonomics for system analysis and product development "in order to optimise human well-being and overall system performance" ( The course offers the framework of models, concepts, methods and tools of applied ergonomics. Teaching is combined with learning-by-doing and research-based learning.
ObjectiveKnowledge of:
- Principles and rules of applied ergonomic system and product design.
- Methods and tools of ergonomic analysis and evaluation.
Practical experiences and hands-on skills in:
- Conducting a study in system and task analysis.
- Analysing human-product interactions.
- Applying ergonomic knowledge for product and system improvements.
Content- Definition and role of applied ergonomics in engineering and design.
- Framework of ergonomic analysis and design.
- Design principles and rules.
- Methods and tools for system and task analysis.
Hands-on experience in team work:
- Experimental study of human-product interaction and usability through eye-tracking
- Field study of system and task analysis, including on-site visits of complex work stations (Hospital OR/ICU or Air traffic/Railway Control Rooms).
Lecture notesHandout at the start of the course.
LiteratureAhlstrom, V. and Longo, V. (2003). Human Factors Design Standard (HFDS).
Wiklund M.E., Wilcox, S.B. (2005). Designing Usability into Medical Products. Taylor & Francis.
Rubin, J. and Chisnell, D. (2008). Handbook of Usability Testing: How to Plan, Design and Conduct Effective Tests. Wiley.
Hölscher, U., Laurig, W. & Müller-Arnecke, H.W. (2008). Prinziplösungen zur ergonomischen Gestaltung von Medizingeräten. BAUA Forschung Projekt F1902.
Niku, S.B. (2009). Creative Design of Products and Systems (Chapter 8). Wiley.
Prerequisites / NoticeMax. number of participants is 15.
Experiments and field studies in teams of 2-3 students are obligatory.
151-3209-00LEngineering Design Optimization Restricted registration - show details
Number of participants limited to 35.
W4 credits4GK. Shea, T. Stankovic
AbstractThe course covers fundamentals of computational optimization methods in the context of engineering design. It develops skills to formally state and model engineering design tasks as optimization problems and select appropriate methods to solve them.
ObjectiveThe lecture and exercises teach the fundamentals of optimization methods in the context of engineering design. After taking the course students will be able to express engineering design problems as formal optimization problems. Students will also be able to select and apply a suitable optimization method given the nature of the optimization model. They will understand the links between optimization and engineering design in order to design more efficient and performance optimized technical products. The exercises are MATLAB based.
Content1. Optimization modeling and theory 2. Unconstrained optimization methods 2. Constrained optimization methods - linear and non-linear 4. Direct search methods 5. Stochastic and evolutionary search methods 6. Multi-objective optimization
Lecture notesavailable on Moodle
363-1065-00LDesign Thinking: Human-Centred Solutions to Real World Challenges Restricted registration - show details
Due to didactic reasons, the number of participants is limited to 30.

All interested students are invited to apply for this course by sending a one-page motivation letter until 14.9.16 to Florian Rittiner (

Additionally please enroll via mystudies. Places will be assigned after the first lecture on the basis of your motivation letter and commitment for the class.
W5 credits5GA. Cabello Llamas, F. Rittiner, S. Brusoni, C. Hölscher, M. Meboldt
AbstractThe goal of this course is to engage students in a multidisciplinary collaboration to tackle real world problems. Following a design thinking approach, students will work in teams to solve a set of design challenges that are organized as a one-week, a three-week, and a final six-week project in collaboration with an external project partner.

Information and application:
ObjectiveDuring the course, students will learn about different design thinking methods and tools. This will enable them to:
- Generate deep insights through the systematic observation and interaction of key stakeholders.
- Engage in collaborative ideation with a multidisciplinary (student) team.
- Rapidly prototype and iteratively test ideas and concepts by using various materials and techniques.
ContentThe purpose of this course is to equip the students with methods and tools to tackle a broad range of problems. Following a Design Thinking approach, the students will learn how to observe and interact with key stakeholders in order to develop an in-depth understanding of what is truly important and emotionally meaningful to the people at the center of a problem. Based on these insights, the students ideate on possible solutions and immediately validated them through quick iterations of prototyping and testing using different tools and materials. The students will work in multidisciplinary teams on a set of challenges that are organized as a one-week, a three-week, and a final six-week project with an external project partner. In this course, the students will learn about the different Design Thinking methods and tools that are needed to generate deep insights, to engage in collaborative ideation, rapid prototyping and iterative testing.

Design Thinking is a deeply human process that taps into the creative abilities we all have, but that get often overlooked by more conventional problem solving practices. It relies on our ability to be intuitive, to recognize patterns, to construct ideas that are emotionally meaningful as well as functional, and to express ourselves through means beyond words or symbols. Design Thinking provides an integrated way by incorporating tools, processes and techniques from design, engineering, the humanities and social sciences to identify, define and address diverse challenges. This integration leads to a highly productive collaboration between different disciplines.

For more information and the application visit:
Prerequisites / NoticeClass attendance and active participation is crucial as much of the learning occurs through the work in teams during class. Therefore, attendance is obligatory for every session. Please also note that the group work outside class is an essential element of this course, so that students must expect an above-average workload.
Multidisciplinary Courses
The students are free to choose individually from the entire course offer of ETH Zurich, ETH Lausanne and the Universities of Zurich and St. Gallen.
» Course Catalogue of ETH Zurich
Semester Project
151-1002-00LSemester Project Mechanical Engineering Restricted registration - show details
Only for Mechanical Engineering MSc.

The subject of the Semester Project and the choice of the supervisor (ETH-professor) are to be approved in advance by the tutor.
O8 credits17AProfessors
AbstractThe semester project is designed to train the students in the solution of specific engineering problems. This makes use of the technical and social skills acquired during the master's program. Tutors propose the subject of the project, elaborate the project plan, and define the roadmap together with their students, as well as monitor the overall execution.
ObjectiveThe semester project is designed to train the students in the solution of specific engineering problems. This makes use of the technical and social skills acquired during the master's program.
Industrial Internship
151-1003-00LIndustrial Internship Mechanical EngineeringO8 creditsexternal organisers
AbstractThe main objective of the 12-week internship is to expose master's students to the industrial work environment. During this period, students have the opportunity to be involved in on-going projects at the host institution.
ObjectiveThe main objective of the 12-week internship is to expose master's students to the industrial work environment.
GESS Science in Perspective
» see GESS Science in Perspective: Type A: Enhancement of Reflection Capability
» see GESS Science in Perspective: Language Courses ETH/UZH
» Recommended GESS Science in Perspective (Type B) for D-MAVT.
Master's Thesis
151-1001-00LMaster's Thesis Mechanical Engineering Restricted registration - show details
Students who fulfill the following criteria are allowed to begin with their Master's Thesis:
a. successful completion of the bachelor program;
b. fulfilling of any additional requirements necessary to gain admission to the master programme;
c. successful completion of the semester project and industrial internship;
d. achievement of 28 ECTS in the category "Core Courses".

The Master's Thesis must be approved in advance by the tutor and is supervised by a professor of ETH Zurich.
To choose a titular professor as a supervisor, please contact the D-MAVT Student Administration.
O30 credits64DProfessors
AbstractMaster's programs are concluded by the master's thesis. The thesis is aimed at enhancing the student's capability to work independently toward the solution of a theoretical or applied problem. The subject of the master's thesis, as well as the project plan and roadmap, are proposed by the tutor and further elaborated with the student.
ObjectiveThe thesis is aimed at enhancing the student's capability to work independently toward the solution of a theoretical or applied problem.
Course Units for Additional Admission Requirements
The courses below are only available for MSc students with additional admission requirements.
406-0173-AALLinear Algebra I and II
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-6 credits13RN. Hungerbühler
AbstractLinear algebra is an indispensable tool of engineering mathematics. The course is an introduction to basic methods and fundamental concepts of linear algebra and its applications to engineering sciences.
ObjectiveAfter completion of this course, students are able to recognize linear structures and to apply adequate tools from linear algebra in order to solve corresponding problems from theory and applications. In addition, students have a basic knowledge of the software package Matlab.
ContentSystems of linear equations, Gaussian elimination, solution space, matrices, LR decomposition, determinants, structure of linear spaces, normed vector spaces, inner products, method of least squares, QR decomposition, introduction to MATLAB, applications.
Linear maps, kernel and image, coordinates and matrices, coordinate transformations, norm of a matrix, orthogonal matrices, eigenvalues and eigenvectors, algebraic and geometric multiplicity, eigenbasis, diagonalizable matrices, symmetric matrices, orthonormal basis, condition number, linear differential equations, Jordan decomposition, singular value decomposition, examples in MATLAB, applications.


Gilbert Strang "Introduction to linear algebra", Wellesley-Cambridge Press: Chapters 1-6, 7.1-7.3, 8.1, 8.2, 8.6

A Practical Introduction to MATLAB:

Matlab Primer:
Literature- Gilbert Strang: Introduction to linear algebra. Wellesley-Cambridge Press

- A Practical Introduction to MATLAB:

- Matlab Primer:
406-0353-AALAnalysis III Information
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.

Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
E-4 credits9RM. Soner
AbstractIntroduction to partial differential equations. Differential equations which are important in applications are classified and solved. Elliptic, parabolic and hyperbolic differential equations are treated. The following mathematical tools are introduced: Laplace transforms, Fourier series, separation of variables, methods of characteristics.
ObjectiveMathematical treatment of problems in science and engineering. To understand the properties of the different types of partlial differentail equations.
ContentLaplace Transforms:
- Laplace Transform, Inverse Laplace Transform, Linearity, s-Shifting
- Transforms of Derivatives and Integrals, ODEs
- Unit Step Function, t-Shifting
- Short Impulses, Dirac's Delta Function, Partial Fractions
- Convolution, Integral Equations
- Differentiation and Integration of Transforms

Fourier Series, Integrals and Transforms:
- Fourier Series
- Functions of Any Period p=2L
- Even and Odd Functions, Half-Range Expansions
- Forced Oscillations
- Approximation by Trigonometric Polynomials
- Fourier Integral
- Fourier Cosine and Sine Transform

Partial Differential Equations:
- Basic Concepts
- Modeling: Vibrating String, Wave Equation
- Solution by separation of variables; use of Fourier series
- D'Alembert Solution of Wave Equation, Characteristics
- Heat Equation: Solution by Fourier Series
- Heat Equation: Solutions by Fourier Integrals and Transforms
- Modeling Membrane: Two Dimensional Wave Equation
- Laplacian in Polar Coordinates: Circular Membrane, Fourier-Bessel Series
- Solution of PDEs by Laplace Transform
LiteratureE. Kreyszig, Advanced Engineering Mathematics, John Wiley & Sons, 10. Auflage, 2011

C. R. Wylie & L. Barrett, Advanced Engineering Mathematics, McGraw-Hill, 6th ed.

G. Felder, Partielle Differenzialgleichungen für Ingenieurinnen und Ingenieure, hypertextuelle Notizen zur Vorlesung Analysis III im WS 2002/2003.

Y. Pinchover, J. Rubinstein, An Introduction to Partial Differential Equations, Cambridge University Press, 2005

For reference/complement of the Analysis I/II courses:

Christian Blatter: Ingenieur-Analysis (Download PDF)
Prerequisites / NoticeUp-to-date information about this course can be found at:
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