Course information

Mandatory courses:

CEE foundationsStatisticsScientific Programming
Data scienceMachine learningImage processing
Mathematical modellingETHZ

You have to choose at least one of these courses during your first PhD year. In special cases, the Program Director may approve courses not included on this list. Be aware that you also need to have 4 credits to pass the first year.
This list may not be updated so please check the course site for exact information.

CEE foundations

Advanced composites in Engineering Structures  CIVIL-443 (3 credits) – FALL

The objective of the course is to: 1. Introduce topics in properties, processing, mechanical behavior, characterization, analysis and structural design of Fiber Reinforced Composites 2. Help students develop their research skills through independent investigations on research topics.

Air pollution ENV-409 (5 credits) – SPRING

A survey course describing the origins of air pollution and climate change.

Composites design and innovation CIVIL-464 (3 crédits) – SPRING

The course offers the opportunity to gain practical experience in the characterization of fiber reinforced polymer and manufacturing/production methods for composite structures. The material is presented by lectures and visits to the laboratory. This is mainly a project based – hands on course

Engineering of existing structures, Civil-511 (4 credits) – FALL

The engineering of existing structures encompasses the examination of condition and load-carrying capacity, decision criteria, and methods for rehabilitation or strengthening. This course presents the bases necessary for this approach at the level of materials and structural response.

Fate and behaviour of environmental contaminants ENV-507 (4 credits) – SPRING

The student will learn the important processes that control the transport and transformation of organic chemicals in the environment, as well as the formulation and solution of quantitative models to describe these processes.

Image processing for earth observation  ENV-540 (4 credits) – FALL

This course covers optical remote sensing from satellites and airborne platforms. The different systems are presented. The students will acquire skills in image processing and machine learning to extract end-products, such as land cover or risk maps, from the images.

Science of Climate Change ENV-410 ( 4 credits) – Fall

The course equips students with a comprehensive scientific understanding of climate change covering a wide range of topics from physical principles, historical climate change, greenhouse gas emissions, the IPCC assessment to future scenarios and climate action

Selected topics in mechanics of solids and structures CIVIL-527  (3 credits) – FALL

The class covers the fundamentals of wave dynamics and fracture mechanics. The aim is to deepen their knowledge in advanced topis in mechanics of solids and structures and discuss current research topics. Case studies on catastrophic failure will be presented and discussed in class.

Structural stability  CIVIL-369 (4 credits) – SPRING

Advanced topics in structural stability; elastic & inelastic column buckling; beam-columns; lateral-torsional buckling of bridge girders; nonlinear geometric effects; frame stability; computational formulation of stability theory; stiffness & flexibility methods

Water and wastewater treatment ENV-405 (5 credits) – FALL

This course on water and wastewater treatment shows how to implement and design different methods and techniques to eliminate organic matter, nitrogen and phosporous from wastewater, and how to apply physical and chemical methods and techniques to produce drinking water.


Biostatistics  MATH-449: (5 credits) – SPRING

Statistics for life sciences – seems to cover a lot of basic statistic information that was present in the cancelled courses so it may still be relevant.

Multivariate statistics with R   ENV-513 (4 credits) – FALL

Data required for ecosystem assessment is typically multidimensional. Multivariate statistical tools allow us to summarize and model multiple ecological parameters. This course provides a conceptual introduction and guidelines for the use of multivariate statistical tools using the R platform.

Sensing and spatial modeling for earth observation ENV-408 (5 credits) – SPRING

In this course students get acquainted with the process of image (orthophoto and DEM) creation, as well as with methods for monitoring the Earth surface using remotely sensed data. Methods will span from machine learning to geostatistics and model the spatiotemporal variability of processes.

Understanding statistics and Experimental design  BIO-449 (4 credits) – FALL

This course is neither an introduction to the mathematics of statistics nor an introduction to a statistics program such as R. The aim of the course is to understand statistics from its experimental design and to avoid common pitfalls of statistical reasoning. There is space to discuss ongoing work.

Scientific Programming

Scientific programming for engineers  MATH-611 (4 credits) – FALL

The students will acquire a solid knowledge on the processes necessary to design, write and use scientific software, including the analysis of results. Modeling aspects, which constrain software design, will lead the students to algorithmic and complexity concepts inherent to all numerical calculation.

Data science

Applied data analysis  CS-401 (8 credits) – FALL

This course introduces the key concepts and algorithms from the areas of information retrieval, data mining and knowledge bases, which constitute the foundations of today’s Web-based distributed information systems.

Distributed information systems  CS-423 (6 credits) – FALL

This course introduces the key concepts and algorithms from the areas of information retrieval, data mining and knowledge bases, which constitute the foundations of today’s Web-based distributed information systems.

Systems for data management and data science  CS-460 (8 credits) – SPRING

This course is intended for students who want to understand modern large-scale data analysis systems and database systems. The course covers fundamental principles for understanding and building systems for managing and analyzing large amounts of data. It covers a wide range of topics and technologi

Machine learning

Applied machine learning  MICRO-455 (4 credits) – FALL

Real-world engineering applications must cope with a large dataset of dynamic variables, which cannot be well approximated by classical or deterministic models. This course gives an overview of methods from Machine Learning for the analysis of non-linear, highly noisy and multi dimensional data.

Deep learning EE-559 (4 credits) – SPRING

The objective of this course is to provide a complete introduction to deep machine learning. How to design a neural network, how to train it, and what are the modern techniques that specifically handle very large networks.

Machine learning CS-433 (8 credits) – FALL

Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analyzed and practically implemented.

Machine learning for Engineers EE-613 (4 credits) – FALL

The objective of this course is to give an overview of machine learning techniques used for real-world applications, and to teach how to implement and use them in practice. Laboratories will be done in python using jupyter notebooks.

Image processing

Image analysis and pattern recognition  EE-451 (4 credits) – SPRING

This course gives an introduction to the main methods of image analysis and pattern recognition.

Visual intelligence: machines and minds CS-503 (6 credits) – SPRING

The course will discuss classic material as well as recent advances in computer vision and machine learning relevant to processing visual data. The primary focus of the course will be on embodied intelligence and perception for active agents.

Mathematical modelling

Mathematical modelling of behaviour  MATH-463 (5 credits) – FALL

Discrete choice models allow for the analysis and prediction of individuals’ choice behavior. The objective of the course is to introduce both methodological and applied aspects, in the field of marketing, transportation, and finance.

Optimization and simulation  MATH-600 (4 credits) – SPRING

Master state-of-the art methods in discrete optimization and simulation. Work involves: – reading the material beforehand – class hours to discuss the material and solve problems – homework

Courses at ETHZ

Applied Analysis of Variance and Experimental Design

Principles of experimental design, one-way analysis of variance, contrasts and multiple comparisons, multi-factor designs and analysis of variance, complete block designs, Latin square designs, random effects and mixed effects models, split-plot designs, incomplete block designs, two-series factorials and fractional designs, power.

Design of Experiments

The course introduces ‘classical’ statistical design of experiments, particularly designs for blocking, full and fractional factorial designs with confounding, and response surface methods. Topics covered include (restricted) randomization and blocking, sample size and power calculations, confounding, and basics of analysis-​of-variance methods for analysis including random effects and nesting.


How can I get credits from courses?

  • See the EDCE regulations about credit allocation.
  • No credits can be obtained from Bachelor courses
  • Maximum 4 credits can be obtained from transversal skill courses
  • Credits from EPFL master courses, which are not in the mandatory courses list, needs to be pre-approved by the theis director and the director of the doctoral program, send an email with your request to the EDCE office.
  • Courses given at other universities, including short courses and summer – winter schools, must be pre-approved by the thesis director and the director of the doctoral program.
    Fill in the request, upload the form here, and send it, signed by your thesis director, to the EDCE office well in advance before the course starts.
    Note that the number of ECTS credits proposed by the course organizer does not necessarily correspond to the number of ECTS credits awarded by the doctoral program. A one week course grants 1 credit. We don’t grant any credits for courses shorter than one week.
    The credits will be awarded only after the reception of an official transcript describing explicitly that an exam was passed, (a certificate of participation is not sufficient) and providing the exact number of proposed ECTS credits.
  • No credits can be obtained from conferences, seminars, symposium, workshops, internships, etc.

I have a 4 year Bachelor degree and have to take extra credits, what are the rules?

We ask for 8 extra credits, resulting in 20 total credits throughout the PhD. Of the extra credits, 4 have to be taken the first year (in addition to the 4 credits required by EDOC). The thesis director must send a proposal with the planned courses to the EDCE office when starting the doctoral school. This proposal must be validated by the program director.

How to know the number of credits?

EDCE program regulation, section 2:

EDCE external course list

These are lists of courses followed by oher EDCE Phd students, its main purpose is to help you find interesting courses that you can’t find at EPFL


Course nameLocation
Applied analysis of variance and experimental designETHZ
Applied Statistical RegressionETHZ
Applied statistics for Ph.D studentsUniversity of Zürich
Designing experiments on the hyporheic zoneUniversity of Birmingham
Environmental data miningUNIL
Introduction to statisticsSwiss institute of bioinformatics
Méthodes statistiques: théories et applicationsUNIL
Statistics for experimental researchETHZ
Uncertainty and sensitivity analysis of numerical modelsDTU, Denmark
Using R for Data Analysis and GraphicsETHZ
Introduction to spatial analysis of ecological data using RPR statistics head-office, Glasgow, scotland

Specialized experimental methods

Course nameLocation
3D VisionETHZ
Combining Structural & Analytical Investigations of Matter at the Micro-, nano- and Atomic ScalesCCMX, Lausanne
Cook and look: Synchroton techniquesETHZ
DIA/SWATH course, Mass spectrometryETHZ
Ecole d’automne de techniques laser pour la mécanique de fluidesLa Rochelle, FR
Mass spectrometry School in Biotechnology and MedicineDubrovnik, summer school
Microbial biofilm techniquesDTU, Denmark
Modern mass spectrometry, Hyphenated methods, and chemometricsETHZ
Sampling in hyporheic zones, in situ measurement techniquesUniversity of Birmingham
Spectroscopy of the earth systemUniversity of Zürich


Course nameLocation
Computable general equilibrium in climate and energy economicsUNIBE
Environmental crisis and society changeUNIL
Swiss program for beginning of doctoral studies in economic macroeconomicsStudy center Gerzensee
Swiss program for beginning of doctoral studies in economic microeconomicsStudy center Gerzensee

General Civil and Environmental Engineering courses

Course nameLocation
Aerosol I: Physical and Chemical principlesETHZ
Analysis of climate and weather dataETHZ
Arctic environmental toxicologyUniversity center in Svalbard, Norway
Atmospheric general circulation dynamicsETHZ
Boundary Layer MeteorologyETHZ
Concrete with Supplementary cementitious materialsDTU, Lyngby, Denmark
Current topics in Grassland SciencesETHZ
DGPT Molecular cell toxicologyZurich University
Environmental and Human Health Risk Assessment of ChemicalsETHZ
Environmental systems analysisEAWAG, summer school, switzerland
EURO Ph.D school on routing and logisticsUniversity of Brescia, Italy
Fragrance chemistryETHZ
Frontiers in plant sciences, application of stable isotopes in plant sciencesETHZ
Geomonitoring and GeosensorsETHZ
Global change biologyETHZ
HypobasicsLeibniz institue of freshwater ecology and inland fisheries, Berlin
Infectious disease dynamicsETHZ
Marges aridesUNIL
Material recovery methods and TechnologiesFHNW, Muttenz, CH
Mechanical and Physics of fracture: Multi-scale Modeling of the failure behaviour of SolidsInternational center for Mechanical Sciences, Udine, Italy
Microbiology and disposal of radioactive wasteETHZ
Modern pesticides – Mode of action, Residus and Environmental FateETHZ
Nanomaterials in the EnvironmentETHZ
Physical chemistryETHZ
Physical LimnologyUniversity of Heidelberg
Physics as a basis for modelingUNIL
Plant-atmosphere interactions in a changing climateGöteborgs universitet, Sweden
Project INFRASTAR fatigue and risk analysis of structuresBAM, Berlin
Quantitative flow visualizationETHZ
Quantitative microbial risk assessmentMichigan State University, USA
Resevoir GeomechanicsStanford university
Seismic response and analysis of structuresUME school Pavia, Italy
Selected chapters in BioinformaticsUNIGE
Shaping the energy transitionSCCER school, Switzerland
Snowcover: physics and modelingETHZ
Summer school of fluvial geomorphologyETHZ
System models in life cycle assessment, summer schoolETHZ
Tropospheric ChemistryETHZ
Virology: Principles of molecular biology, pathogenesis and control of human virusesUniversity of Zürich
Virus-host InteractionsUNIL
Visions for sustainable agricultureUNINE
Water resources and drinking waterETHZ
Winter school on the observation and modeling of high-latitude and Arctic CloudsFinland

EDCE external transversal skills list

Course nameLocation
Discovering managementETHZ
Environmental communication teachingCampus virtual ISM, Spain
Reading in environmental thinkingETHZ
Research ethicsETHZ
Responsible conduct in researchETHZ

Interesting sites for courses:
Swiss Institute of Bioinformatics
EMBO – Excellence in the life sciences.

This list includes doctoral courses only, master courses are not listed. 
All external courses are subject to approval by the thesis director and the doctoral school. Contact the EDCE office for all external courses.
Listed credits may not correspond to the number of credits awarded by EPFL.
Check if an equivalent course at EPFL exists.
Courses on the list may not longer be taught.