STI –PhD position in AI-based Optimization for Ultrasonic Motor

Updated: about 1 month ago

The Integrated Actuators Laboratory (Prof. Perriard ) is looking for a PhD researcher who is highly motivated towards addressing the challenges in Tribological phenomena in Ultrasonic Ceramic Motor (UCM). The project may in particular attract candidates with an engineering background who aspire to explore a cutting-edge multidisciplinary subject involving Artificial Intelligence (AI) and Topology Optimization. You will have to implement state-of-the-art modeling techniques to capture the complex Tribological interactions that govern Ultrasonic Ceramic Motors. You will have access to experimental data from UCM applications for AI model training and conduct experiments to validate your models on a unique test bench.


Key responsibilities: 
  • Build Tribological models for Ultrasonic Motors
  • Design Topological Optimization algorithm
  • Carry out AI training with tribological data

Your profile
  • MSc degree in microengineering, electrical engineering, mechatronics or similar
  • Some background in artificial intelligent is a plus
  • Motivation for multidisciplinary research and team projects
  • Excellent spoken and written English
  • Self-motivated, creative and enthusiastic

What we have to offer
  • An opportunity to work on cutting-edge projects in actuations within a world-class community of engineers and scientists
  • A dynamic, multidisciplinary, international and collaborative working environment based at Microcity in Neuchâtel
  • We offer a competitive salary and benefit, defined by EPFL scales and regulations

Application process

Your application should be submitted as one single pdf file containing:

  • Motivation Letter
  • Detailed CV
  • Contact information
  • At least 2 references willing to write a recommendation letter. Letters of recommendation should be sent back by the same deadline
  • Start date: As soon as possible
  • Application deadline: October 30, 2022
  • Please send your application to: xiaotao.ren@epfl.ch
  • For more information, please contact: Xiaotao Ren

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