PhD in Machine Learning for Quantum Systems
Join Leiden University to research interpretable and reliable machine learning methods for quantum many-body physics.
Best for:Best for master's graduates in physics or computer science with a strong interest in quantum systems and Python programming.
Overview
Leiden University is offering a fully-funded PhD position focusing on the intersection of machine learning and quantum many-body physics within the Interpretable Machines for Physics research group. Working under the supervision of Dr. Anna Dawid, the successful candidate will develop interpretable, reliable, and scalable machine learning approaches for complex quantum problems. The role combines deep learning research with structured mentorship, scientific freedom, and participation in the interdisciplinary Applied Quantum Algorithms group. Candidates will also engage in limited teaching duties, co-supervise students, and present their findings at international conferences.
What you'll do
- Conduct rigorous academic research on the mechanics of deep learning and its applications in quantum sciences under supervision.
- Develop interpretable, reliable, and scalable machine learning approaches for challenging quantum problems.
- Participate in regular individual and group research meetings, sharing progress and insights.
- Assist with departmental teaching activities and help co-supervise bachelor and master students.
- Co-organize scientific events and present research outcomes at international conferences and through publications.
Requirements
Degree required: Master’s degree in physics, computer science, or a closely related field
Degree offered: PhD
Language: English; proficient in spoken and written English
Instruction: English
- Strong interest in machine learning and motivation to make models interpretable and reliable
- Proficiency in Python programming
- Ability to work collaboratively as part of an interdisciplinary team
- Highly motivated, organized self-starter approach with an open mindset
Funding & terms
How to apply
Deadline: 2026-11-30
Submit your application online through the university vacancy portal using the designated application button. Ensure all requested supporting documentation, including your CV, motivation letter, and optional research statement, are properly uploaded before the deadline.
- CV
- Cover letter
- Research statement
- Reference contacts
Contact
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.