Course information
Mandatory courses:
CEE foundations – Statistics – Scientific Programming
Data science – Machine learning – Image processing
Mathematical modelling – ETHZ
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.
Fourier analysis and boundary value problems ENV-614 (4 credits) – SPRING
Learning Fourier Series and Boundary Value Problems with a view to a variety of science and engineering problems. Learn the use of special functions like Bessel functions and applications. Introduce the doctoral students to general Sturm-Liouville problems and applications.
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.
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.
Statistics
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 (5 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
Summary
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.
Summary
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.
FAQ
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.
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.
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. The general rule is that a 5-day course is worth 1 ECTS.
- 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.
About PhD courses
https://www.epfl.ch/education/phd/doctoral-studies-structure/doctoral-courses/edoc-about-phd-courses
How to know the number of credits?
EDCE program regulation, section 2: https://www.epfl.ch/education/phd/regulations/doctoral-programs-regulations
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
Statistics
| Course name | Location |
| Applied analysis of variance and experimental design | ETHZ |
| Applied Statistical Regression | ETHZ |
| Applied statistics for Ph.D students | University of Zürich |
| Designing experiments on the hyporheic zone | University of Birmingham |
| Environmental data mining | UNIL |
| Introduction to statistics | Swiss institute of bioinformatics |
| Méthodes statistiques: théories et applications | UNIL |
| Statistics for experimental research | ETHZ |
| Uncertainty and sensitivity analysis of numerical models | DTU, Denmark |
| Using R for Data Analysis and Graphics | ETHZ |
| Introduction to spatial analysis of ecological data using R | PR statistics head-office, Glasgow, scotland |
Specialized experimental methods
| Course name | Location |
| 3D Vision | ETHZ |
| Combining Structural & Analytical Investigations of Matter at the Micro-, nano- and Atomic Scales | CCMX, Lausanne |
| Cook and look: Synchroton techniques | ETHZ |
| DIA/SWATH course, Mass spectrometry | ETHZ |
| Ecole d’automne de techniques laser pour la mécanique de fluides | La Rochelle, FR |
| Mass spectrometry School in Biotechnology and Medicine | Dubrovnik, summer school |
| Microbial biofilm techniques | DTU, Denmark |
| Modern mass spectrometry, Hyphenated methods, and chemometrics | ETHZ |
| Sampling in hyporheic zones, in situ measurement techniques | University of Birmingham |
| Spectroscopy of the earth system | University of Zürich |
Economics
| Course name | Location |
| Computable general equilibrium in climate and energy economics | UNIBE |
| Environmental crisis and society change | UNIL |
| Swiss program for beginning of doctoral studies in economic macroeconomics | Study center Gerzensee |
| Swiss program for beginning of doctoral studies in economic microeconomics | Study center Gerzensee |
General Civil and Environmental Engineering courses
| Course name | Location |
| Aerosol I: Physical and Chemical principles | ETHZ |
| Analysis of climate and weather data | ETHZ |
| Arctic environmental toxicology | University center in Svalbard, Norway |
| Atmospheric general circulation dynamics | ETHZ |
| Boundary Layer Meteorology | ETHZ |
| Concrete with Supplementary cementitious materials | DTU, Lyngby, Denmark |
| Current topics in Grassland Sciences | ETHZ |
| DGPT Molecular cell toxicology | Zurich University |
| Environmental and Human Health Risk Assessment of Chemicals | ETHZ |
| Environmental systems analysis | EAWAG, summer school, switzerland |
| EURO Ph.D school on routing and logistics | University of Brescia, Italy |
| Fragrance chemistry | ETHZ |
| Frontiers in plant sciences, application of stable isotopes in plant sciences | ETHZ |
| Geomonitoring and Geosensors | ETHZ |
| Global change biology | ETHZ |
| Hypobasics | Leibniz institue of freshwater ecology and inland fisheries, Berlin |
| Infectious disease dynamics | ETHZ |
| Marges arides | UNIL |
| Material recovery methods and Technologies | FHNW, Muttenz, CH |
| Mechanical and Physics of fracture: Multi-scale Modeling of the failure behaviour of Solids | International center for Mechanical Sciences, Udine, Italy |
| Microbiology and disposal of radioactive waste | ETHZ |
| Modern pesticides – Mode of action, Residus and Environmental Fate | ETHZ |
| Nanomaterials in the Environment | ETHZ |
| Physical chemistry | ETHZ |
| Physical Limnology | University of Heidelberg |
| Physics as a basis for modeling | UNIL |
| Plant-atmosphere interactions in a changing climate | Göteborgs universitet, Sweden |
| Project INFRASTAR fatigue and risk analysis of structures | BAM, Berlin |
| Quantitative flow visualization | ETHZ |
| Quantitative microbial risk assessment | Michigan State University, USA |
| Resevoir Geomechanics | Stanford university |
| Seismic response and analysis of structures | UME school Pavia, Italy |
| Selected chapters in Bioinformatics | UNIGE |
| Shaping the energy transition | SCCER school, Switzerland |
| Snowcover: physics and modeling | ETHZ |
| Summer school of fluvial geomorphology | ETHZ |
| System models in life cycle assessment, summer school | ETHZ |
| Tropospheric Chemistry | ETHZ |
| Virology: Principles of molecular biology, pathogenesis and control of human viruses | University of Zürich |
| Virus-host Interactions | UNIL |
| Visions for sustainable agriculture | UNINE |
| Water resources and drinking water | ETHZ |
| Winter school on the observation and modeling of high-latitude and Arctic Clouds | Finland |
EDCE external transversal skills list
| Course name | Location |
| Discovering management | ETHZ |
| Environmental communication teaching | Campus virtual ISM, Spain |
| Reading in environmental thinking | ETHZ |
| Research ethics | ETHZ |
| Responsible conduct in research | ETHZ |
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.