Pre-doctoral researcher

Quantum simulations and quantum machine learning for materials science

Ref. 2022_039

Job Description

Simulation and machine learning methods represent nowadays, together with theory and experiments, one of the pillars of modern science. At the forefront of computational physics, the study of many-body quantum systems offers the possibility to address open questions in fundamental research and to develop new technological solutions by leveraging advanced quantum information processing protocols.

In this PhD project, we will integrate digital quantum simulations and quantum machine learning in the context of materials science. The starting point will be the realisation of robust digital simulation techniques with noisy quantum computers, featuring error mitigation, optimal circuit compilation strategies and direct hardware control at the pulse level. We aim at bringing noisy gate-based quantum processors to challenge the best available classical methods (e.g., tensor networks), paralleling similar efforts conducted with analog quantum simulators in the realm of ~100 qubit systems.

Specific targets will be spin chains/lattices, as well as 2D and multi-band versions of the Hubbard model. As a route towards applications, embedding techniques combining classical and quantum computations, as well as Green’s functions methods, will be explored. At the same time, an integral part of the project will focus on the use of advanced quantum machine learning functionalities to analyse and verify the output of quantum simulations and electronic structure calculations directly at the wavefunction level. By natively accessing quantum data, these tools could allow effective learning of entanglement structures and physical properties, quantum phase detection and materials classification, thus opening new directions for the development of database-driven materials discovery workflows.

The research will encompass theoretical analysis, development of new methods as well as practical algorithm implementation and execution on state-of-the-art IBM Quantum superconducting processors. This project is part of the NCCR MARVEL initiative. The expected starting date is early 2023.


  • Master's degree in Physics, Chemistry or a related area
  • Background and strong interest in quantum information and quantum computing
  • Familiarity with computational physics, condensed matter physics and materials science

Preferred qualifications

We are looking for an independent researcher with an enquiring, critical mind. In addition to the requirements listed above, the following skills are also considered nice to have:
  • Knowledge of quantum simulation algorithms and corresponding classical methods (e.g., tensor networks)
  • Knowledge of quantum and classical machine learning and related applications in natural sciences
  • Experience with Python and Qiskit, as well as research-driven code development, numerical techniques, and general programming concepts
  • Excellent communication skills


IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent flexible working arrangements enable all genders to strike the desired balance between their professional development and their personal lives.

How to apply

If you are interested, please submit your application below.