PhD in Machine Learning for Quantum Systems

at  Universiteit Leiden

Vacancy number
15228
Job type
PhD positions
Hours (in fte)
1,0
External/ internal
External
Location
Leiden
Placed on
22 October 2024
Closing date
24 November 2024 33 more days to apply
The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for candidates for a:

PHD IN MACHINE LEARNING FOR QUANTUM SYSTEMS (1.0 FTE)

We are looking for Ph.D. candidates interested in research at the intersection of machine learning (ML) and quantum many-body physics.
The successful candidate will work with Dr. Anna Dawid on developing new ML approaches to challenging quantum problems, with a strong focus on making these approaches interpretable, reliable, and scalable. In this position, you will learn about state-of-the-art deep learning solutions as well as the challenges of building and working with quantum platforms such as ultracold Rydberg quantum simulators. You will be given an increasing amount of scientific freedom supported by structured mentoring that includes career development plans guided by your plans after the PhD. The starting date is flexible, the latest in October 2025.
The position is set in the exciting, friendly, and interdisciplinary environment of the aQa (applied quantum algorithms) group, which is a team of faculty, postdoctoral researchers, and students across the Leiden Institute for Advanced Computer Science (LIACS), the Leiden Institute of Physics (LION), the Leiden Institute for Chemistry (LIC), and the Leiden Mathematical Institute (MI) at the Leiden University.

• Conducting research on applications of (interpretable, reliable, and scalable) ML in quantum sciences with scientific integrity and rigor under the supervision of Dr. Anna Dawid.
• Assisting in relevant teaching activities.
• Actively participating in regular group and one-on-one meetings.
• Co-supervising Bachelor or Master students.
• Presenting your research results to the scientific community at international conferences and through publications.