PhD Researcher in Physical Learning Machines

2 weken geleden


Amsterdam, Noord-Holland, Nederland AMOLF Voltijd
About the Position

We are seeking a highly motivated PhD researcher to join our team at AMOLF, working on the development of fundamental understanding and theories regarding learning in physical systems. The successful candidate will be part of the Learning Machines group, led by Dr. Menachem Stern, and will focus on the theoretical understanding of physical learning and physically realizable learning rules.

Key Responsibilities
  • Conduct research on learning in physical systems, including analytical and computational modeling of physically and biologically inspired systems.
  • Develop and characterize physical methods by which such systems can learn.
  • Collaborate with the group leader and other researchers at AMOLF to design and realize computational models of physical learning.
  • Contribute to the development of new methods for learning in physical systems, with a focus on connecting these ideas to real-life biological learning systems.
Requirements
  • Master's degree in physics, biophysics, electrical/mechanical engineering, materials science, or computer science.
  • Strong background in physics, biophysics, or a related field.
  • Excellent communication and teamwork skills.
  • Experience with coding (Python/Matlab) and numerical methods is an advantage.
What We Offer
  • A full-time PhD position for four years.
  • A competitive salary and benefits package.
  • The opportunity to work in a dynamic and international research environment.
  • Access to state-of-the-art facilities and resources.
How to Apply

To apply, please submit your resume and a motivation letter (max. 1 page) explaining why you are interested in this position and how your skills and experience align with the requirements. Applications will be evaluated on a rolling basis, and the position will be filled as soon as an excellent match is made.



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