The postdoc will work at UiO with Massel and Hjorth-Jensen, focusing on theoretical and algorithmic developments that enable machine-learning-assisted discovery, control, and certification of complex multimode quantum states. The work will interface closely with experimental partners (ETH Zürich, Aalto University) and theory partners (TU Darmstadt, Palacký University).

Main work tasks may include (depending on profile and project needs):

• Develop ML-assisted Hamiltonian discovery/engineering methods for multimode bosonic and hybrid quantum systems (including open-system and non-Hermitian effects).
• Design noise-resilient control and optimization strategies, including reinforcement learning (RL) and optimal control approaches for state preparation and measurement protocol design under hardware constraints.
• Develop open-source software and documented benchmarks.
• Co-author high-quality publications and contribute to consortium deliverables and reporting; participate in partner visits, workshops, and training activities.

For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/305567/postdoctoral-research-fellow-in-quantum-machine-learning-for-multimode-mechanics

The postdoc will work at UiO with Massel and Hjorth-Jensen, focusing on theoretical and algorithmic developments that enable machine-learning-assisted discovery, control, and certification of complex multimode quantum states. The work will interface closely with experimental partners (ETH Zürich, Aalto University) and theory partners (TU Darmstadt, Palacký University).

Main work tasks may include (depending on profile and project needs):

• Develop ML-assisted Hamiltonian discovery/engineering methods for multimode bosonic and hybrid quantum systems (including open-system and non-Hermitian effects).
• Design noise-resilient control and optimization strategies, including reinforcement learning (RL) and optimal control approaches for state preparation and measurement protocol design under hardware constraints.
• Develop open-source software and documented benchmarks.
• Co-author high-quality publications and contribute to consortium deliverables and reporting; participate in partner visits, workshops, and training activities.

For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/305567/postdoctoral-research-fellow-in-quantum-machine-learning-for-multimode-mechanics