Postdoctoral Position in Applied Machine Learning

Website EPFL

The Ecole Polytechnique Fédérale de Lausanne (EPFL) is one of the most dynamic university campuses in Europe and ranks among the top 20 universities worldwide. The EPFL employs 6,000 people supporting the three main missions of the institutions: education, research, and innovation. The EPFL campus offers an exceptional working environment at the heart of a community of 16,000 people, including over 10,000 students and 3,500 researchers from 120 different countries.
Your mission:
Over the past 10 years, ML/AI has deeply revolutionized fields where data can be easily collected and used to discover complex patterns and relationships that would otherwise escape the human mind. Recent advances in attention-based models, autoencoders, and LSTMs are enabling personalization at scale in applied domains. ML is also transforming research in education, requiring scientists able to bridge between ML and education. Are you interested in developing ML models able to understand and improve human learning? Do you want to join us on the exciting journey of transforming education through high-impact research?
The EPFL Machine Learning for Education laboratory (ML4ED, led by Prof. Tanja Käser) is looking to hire a postdoctoral researcher candidate in applied machine learning. Areas of interest include reinforcement learning, time series modeling, and recommender systems. You will have the opportunity to work in a highly talented and motivated EPFL research group. You will lead innovative projects at the intersection of machine learning and education and be able to directly observe the impact of your research in the field. There will be opportunities to organize and supervise Master’s and Bachelor’s students (individually or in teams) and to mentor Ph.D. students. There will be large-scale computing resources (e.g., 100+ high-memory A100 GPUs) available to execute your agenda.

Main duties and responsibilities include: 
  • Conduct novel research at the intersection of machine learning and education
  • Participate in the supervision of Master’s and Ph.D. students
  • Participate in the writing of articles and other documents related to research activities
  • Participate in the teaching activities of the lab (assistance of exercises, exam correction, supervision of research project students)
  • Support the logistic activities of the lab

Your profile:

Applicants should have completed or be close to completing a Ph.D. in computer science, information science, or other related technical fields. We expect a strong scientific background and a proven publication record in machine learning, natural language processing, artificial intelligence, data mining, or statistics. Prior experience in working with educational data will be considered an asset and an interest in education is a must. Furthermore, we expect excellent communication skills in English.
We offer: 
EPFL ranks among the world’s top universities in computer science, and in machine learning in particular. It is located in Lausanne, Switzerland, a beautiful and vibrant city in an Alpine setting on the shores of scenic Lake Geneva, in the very heart of Europe. EPFL provides an interdisciplinary research setting in digital education, which is unique in Europe. The ML4ED lab is a partner of the EPFL Center for Learning Sciences, which brings together multiple initiatives on digital education. EPFL has produced over 100 MOOCs gathering over 2 million registrations worldwide, opened an extension school, sold over 40’000 robots to schools for learning to program, conducted research on technologies for vocational education, eye tracking, HCI, AR, tangibles, analytics, etc. and produced cutting edge research in many sectors of educational technologies. EPFL is an equal opportunity employer.
Start date: 
The start date is flexible but should be before September 2022.
Term of employment:
Fixed-term (CDD)
1-year renewable (up to 4 years).
For any further questions regarding the position, please contact:
When applying, please upload the following documents:
  • Short Cover letter CV (including list of publications)
  • Two representative publications / preprints
  • Webpage / Google Scholar / Semantic Scholar links
  • Contact information for two willing reference letter writers


Only candidates who applied through EPFL website or our partner Jobup’s website will be considered. Files sent by agencies without a mandate will not be taken into account.
Job Nb 2304
Please apply at (“apply online” button at the bottom of the page).

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