About this role
Summary: Conducts machine learning-based co-design research on aerodynamic shapes and controls, including model glider designs for FAI competitions. Publishes research in top-level machine learning venues.
Mission
The EPFL computer vision lab (https://www.epfl.ch/labs/cvlab/ ) is looking for a postdoctoral fellow to work on issues related to co-design for aerodynamic shape and control along the lines described in the following tech report https://arxiv.org/abs/2603.06760. A potential target application is the design of model gliders to compete in FAI competitions such as https://www.fai.org/page/f5-electric-flight.
Profile
Potential candidates are expected to have:
- A doctorate in a Machine-Learning related field
- A deep knowledge of Control Theory, both classical and deep learning based
- A solid publication record in top level ML venues such as NeurIPs, ICML, and ICLR
- Familiarity with aerodynamics and aircraft design would be a plus
We offer
- A stimulating and international working environment
- Competitive salary and excellent working conditions – more information can be found on our website ([https://www.epfl.ch/campus/services/human-resources/en/basic-starting-salary-of-doctoral-assistants-and-postdocs/)](https://www.epfl.ch/campus/services/human-resources/en/basic-starting-salary-of-doctoral-assistants-and-postdocs/%29)
- Opportunity to perform state-of-the-art research in one of the most dynamic scientific institutions in Europe.
- Opportunity to interact with internationally renowned experts, and with a strong team of postdoctoral researchers and PhD students
Informations
Only applications submitted through the online platform are considered. You are asked to supply:
A brief cover letter (pdf, up to 2 pages).
And in one PDF:
A CV with a publication list.
A research statement (pdf, up to 3 pages).
Contact details for 3 referees.
Contract start date : Flexible (Fall 2026 preferred)
Activity rate : 100%
Contract type : CDD
Duration : One year, renewable