PhD: Interpretable ML for Quantum Systems

Universiteit Leiden; Leiden; Hybrid; EUR 36,000 - 45,000; Full time

Benefits offered by this job

Laptop provided

Hybrid working possible

Job summary

Leiden University invites applications for a PhD in Machine Learning for Quantum Systems (1.0 FTE), based in Leiden. The project is housed in the Interpretable Machines for Physics (IMP) group led by Dr. Anna Dawid and offers mentoring and career development plans, with a flexible starting date up to November 2027.

The successful candidate will explore ML mechanics and develop interpretable, reliable, and scalable ML methods for quantum problems, collaborating across LIACS, LIC, MI, and LION.

Qualifications

• Master's degree in physics, computer science, or a closely related field.
• Strong interest in ML and motivation to make it interpretable and reliable.
• Knowledge of quantum physics and numerical methods for quantum systems or theory of deep learning is preferred.

Responsibilities

• Conducting research on the mechanics of deep learning and 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 and Master students;
• Co-organizing scientific events;
• Presenting your research results to the scientific community at international conferences and through publications.

Skills

Python programming

English proficiency

Team collaboration

Motivated and organized

Strong interest in ML

Education

Master's degree in physics, computer science, or a closely related field

Tools

Python

Job description

Leiden University invites applications for a PhD in Machine Learning for Quantum Systems (1.0 FTE), based in Leiden. The project is housed in the Interpretable Machines for Physics (IMP) group led by Dr. Anna Dawid and offers mentoring and career development plans, with a flexible starting date up to November 2027.

The successful candidate will explore ML mechanics and develop interpretable, reliable, and scalable ML methods for quantum problems, collaborating across LIACS, LIC, MI, and LION.