Program Overview

Introduction to the Joint EPFL – ETH Zurich Doctoral Program in the Learning Sciences (JDPLS)

The Joint EPFL – ETH Zurich Doctoral Program in the Learning Sciences (JDPLS) is an interdisciplinary research area that focuses on developing a multi-faceted understanding of learning as it happens in the real world, as well as designing, implementing, and improving learning environments.

About the Program

The JDPLS educates a new generation of bilingual scientists who will bring together knowledge and methods from multiple disciplines such as psychology, education, computer science, and data science to answer questions of how people learn and hence how to teach in the digital age. This PhD program is directed towards students from any field of science or engineering who are highly motivated towards addressing the challenges in education that arise from the digitization of society. Research in the JDPLS emphasizes bridging the gap between fundamental and translational research. Our doctoral students are trained to lead the transformation in all parts of our education systems, including schools, universities, workplace, and informal learning spaces.

Applying to JDPLS

Applications can be submitted several times a year. The deadlines for submission are prior to April 15 or December 15. Recommendations before submitting an application include:

• Checking out the details on the openings and the candidate profile.
• Checking out how to apply to JDPLS for specific information.
• 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.
• Being aware that only complete applications are reviewed.

Research Areas

Our research explores multiple dimensions of technology-enhanced education aimed at improving teaching and learning processes. It includes the integration of tools like augmented and virtual reality, AI, and robotics to support classroom instruction and real-time classroom management. Another focus is embodied learning, which leverages technologies such as extended reality and haptic feedback to make abstract STEM concepts more accessible through physical interaction and gamification. The research also addresses informal and lifelong learning by designing flexible learning environments.

Career Prospects

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 be hired in teaching-learning centers of universities and interdisciplinary research centers or corporate training departments. Informal learning spaces such as museums and other curated exhibits also hire learning scientists with strong content expertise. Graduates also pursue academic careers, join companies as scientists, or are involved in learning and technology policy-making at various levels.

Program Structure and Community

The JDPLS community includes a variety of experts and researchers from both EPFL and ETH Zurich. The program is led by:

• Prof. Pierre Dillenbourg, EPFL
• Prof. Dr. Manu Kapur, ETH Zurich
• Founding Chair: Prof. Dr. Manu Kapur, ETH Zurich
• Executive Director: Dr. Victoria Abou-Khalil, EPFL

The program's structure and the community's involvement are designed to provide a comprehensive and supportive environment for PhD students to explore their research interests and contribute to the field of learning sciences.

Conclusion

The Joint EPFL – ETH Zurich Doctoral Program in the Learning Sciences offers a unique opportunity for students to engage in interdisciplinary research, focusing on the development of learning environments and the improvement of educational processes. With its emphasis on bridging the gap between fundamental and translational research, the JDPLS prepares its graduates to become leaders in the transformation of education systems, equipped with the knowledge and skills to design, implement, and evaluate innovative educational solutions.