PhD on Quantum Computing × AI for Optimization

Immigration Policy Lab; Zürich; Vor Ort; CHF 50.000 - 70.000; Vollzeit

Benefits dieser Stelle

Freedom to develop research ideas

Opportunity to collaborate internationally

Access to computational facilities

Zusammenfassung

Immigration Policy Lab is inviting applications for a PhD position in Zurich focused on quantum computing and AI for optimization. The role offers collaboration with ETH Zurich and IBM, aiming to advance research at this exciting intersection.

Candidates should hold a Masters degree in relevant fields and possess strong coding, leadership, and collaborative skills. The position promotes a supportive and diverse research environment.

Qualifikationen

• Masters degree in relevant fields such as physics, computer science, or machine learning.
• Interest in optimization methods and quantum computing.
• Strong leadership and coding skills.

Aufgaben

• Develop AI-driven quantum optimization algorithms.
• Collaborate with ETH Zurich and IBM Research.
• Work on theoretical and computational optimization methods.

Kenntnisse

Theoretical or computational methods for optimization

Quantum computing

Machine learning

Coding skills

Leadership skills

Ausbildung

Masters degree in physics, mathematics, applied mathematics, computer science, or related field

Jobbeschreibung

PhD on Quantum Computing × AI for Optimization

100%, Zurich, fixed-term

We invite applications for a PhD position at the intersection of quantum computing and artificial intelligence, focused on the challenge of advancing optimization through both technologies. The position is jointly in collaboration with Stefan Woerner (Principal Research Scientist & Manager, Applied Quantum Science, IBM Research Europe – Zurich) and by Juan Carrasquilla (Institute for Theoretical Physics, Department of Physics, ETH Zurich).

Job description

You will have the opportunity to work across both ETH Zurich and IBM Research Zurich, benefiting from the synergy between academic and industrial research. The topic of the PhD position sits at the crossroads of quantum computing, machine learning, and combinatorial optimization — an area where some of the most exciting and open questions in the field live. Research directions include:

• Using AI to learn parameters and design circuits for quantum optimization algorithms (e.g., beyond QUBO formulations for QAOA)
• Developing AI-driven methods to discover quantum optimization algorithms
• Generating quantum samples to warm‑start classical AI solvers, or to produce quantum-enhanced features and embeddings

The core questions driving this research are fundamental and timely: How can we ensure AI‑discovered quantum algorithms are not classical in disguise? How can we generate large‑scale, high‑quality quantum training data? And how can we combine quantum computing and AI to achieve a measurable, real‑world advantage?

Profile

• A Masters degree in physics, mathematics, applied mathematics, computer science, quantum computing, machine learning
• Strong interest in the development of theoretical or computational methods for optimization methods, quantum computing, and machine learning
• Strong leadership skills
• Strong coding skills
• Ability to collaborate and establish positive interactions with a widely diverse group of people from different backgrounds, countries, ethnicities, genders, etc.
• Ability to work independently and in collaboration

We offer

• Freedom to develop your research ideas and skills
• Opportunity to collaborate with ETH faculty and IBM researchers, as well as internationally
• Mentor students
• Experience a supportive research atmosphere
• Define, jointly with the rest of the team, a work schedule that best fits your preferences and constraints
• Access to state‑of‑the‑art computational facilities

We value diversity and sustainability

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. We also are consistently working towards a climate‑neutral future.