JDPLS – Applicants

Application dead-line/year: April 15th.
Online application form

Admission to the program is on a competitive basis. Candidates will be pre-selected by the learning sciences program committee and have to be accepted by a professor affiliated with the JDPLS, either at EPFL or at ETH Zurich, to be admitted into the program. It’s not necessary to ensure a supervisor before applying for the program, but you can contact faculty members if you wish.  PhD students have a salary as well as course requirements and TA duties. Upon defending their thesis, a graduate will obtain something unique – a joint degree from two premier universities, EPFL and ETH Zurich, both ranked in the top-15 universities in the world. 

  • Profile of a desired candidate

Being an interdisciplinary field, the learning sciences borrows concepts and methods from the physical, biological and social sciences, and engineering domains. In addition, core disciplinary expertise is important for researching teaching and learning in disciplines such as science and engineering. Therefore, this doctoral program will train dual-discipline learning scientists; we seek candidates who have studied a core discipline at the masters’ level (e.g., physics, chemistry, computer science, electrical engineering, psychology) and train them in the learning sciences. This program seeks to leverage their expertise in the core discipline for their research and training in the learning sciences and enable them to research the learning issues in their core disciplines. We seek candidates with a strong motivation to work in and change the field of education. 

  • Admissions process

The applications will be first screened by the JDPLS doctoral committee to identify the admissible list of applicants. This pool of admissible applicants will then be assessed by interested professors, who will choose candidates through interviews. The admission criterion will be a Master degree at the EPF/ETH level. Candidates with a Master degree in another dicipline may be conditionally admitted with the requirement that they complete a stipulated number of extra credits before the candidacy exam, as decided by the program committee at the time of admission and specified in the admission letter. The student will have two co-supervisors, one from each institute, but will register at the institution of the main supervisor, and join the ETH/EPF Joint Doctoral Program in the Learning Sciences (JDPLS). 

  • Expected jobs upon graduation

The joint doctoral program will train learning scientists who upon graduation are experts in the design, implementation and evaluation of educational innovations to improve learning. They can for instance be hired in teaching-learning centers of universities and interdisciplinary research centers such as the CAPE, CEDE or LEARN units at EPFL and the MINT learning center of ETH Zurich. They can also join corporate training departments. Informal learning spaces such as museums and other curated exhibits also hire learning scientists with strong content expertise. These students will also be trained to become professors in universities, and scientists in companies. The graduates can also be involved in learning and technology policy-making at various levels, as well as in one of the thousands of EdTech companies. In Switzerland, the Swiss EdTech Collider gathers no less that 80 start-ups in this field, some with over 100 employees. 

  • How to apply

To apply to the joint doctoral program, please use the EPFL doctoral program application website below. Detailed information about the admission and application procedures, as well as the application forms, and funding is available at:

Please note that applications must be complete by the dead-line to be taken into consideration by the committee (this means with the recommendation letters from your three referees) and that all requested documents should be uploaded directly on the online application. We do not accept these documents by email or post.

For all questions, please contact:

EPFL  [email protected]

ETH Zurich  [email protected]