Quantum Chemistry Lead

Barrington James Limited; Weilheim in Oberbayern; On-site; EUR 120,000 - 180,000; Full time

Job summary

Barrington James Limited is seeking a Team Lead for Quantum Chemistry Algorithms to build and head a team focused on gate-based quantum algorithms for chemistry and correlated materials. You will set the technical direction and translate theory into practical, resource-estimated algorithms.

You will collaborate with hardware specialists to understand how architecture affects performance, own the technical roadmap, and mentor scientists in fault-tolerant approaches such as block encoding and

Qualifications

• PhD in a closely related discipline or equivalent.
• Several years of post-PhD experience in quantum computing, academia or industry.
• Strong experience in development and analysis of quantum algorithms.

Responsibilities

• Build, lead and develop a team of quantum chemistry and quantum algorithm scientists.
• Own the technical roadmap for gate-based quantum algorithms across chemistry and correlated materials.
• Design, analyse and benchmark advanced fault-tolerant quantum algorithms for practical problems.
• Develop algorithms using block encoding, qubitization, quantum signal processing and related techniques.
• Conduct end-to-end quantum resource estimation under realistic error-correction assumptions.
• Foster collaboration between algorithm, hardware and architecture teams for co-design.
• Assess how hardware architecture impacts algorithm performance and feasibility.

Skills

Quantum algorithms

Team leadership

Resource estimation

End-to-end design

Fault-tolerant algorithms

Education

PhD degree

Job description

As Team Lead for Quantum Chemistry Algorithms, you will build and lead a team focused on developing advanced gate-based quantum algorithms for quantum chemistry and correlated materials. This is a highly influential position, sitting at the intersection of quantum algorithms, hardware development, software, and real-world industrial applications.

You will set the technical direction for the team, translating advanced theoretical approaches into practical, resource-estimated algorithms and working closely with hardware specialists to understand how architectural decisions impact end-to-end application performance.

Key Responsibilities

• Build, lead and develop a team of quantum chemistry and quantum algorithm scientists.
• Take ownership of the technical roadmap for gate-based quantum algorithms across quantum chemistry and correlated electronic materials.
• Design, analyse and benchmark advanced fault-tolerant quantum algorithms for application-relevant problems.
• Develop algorithms based on approaches including block encoding, qubitization, quantum signal processing and related fault-tolerant techniques.
• Conduct end-to-end quantum resource estimation, translating theoretical algorithms into realistic computational costs under practical error-correction assumptions.
• Drive close collaboration between algorithm, hardware and architecture teams to ensure effective hardware-software co-design.
• Identify how hardware architecture and platform capabilities can influence algorithm performance and application feasibility.

Requirements

• PhD in Physics, Computer Science, Applied Mathematics, Theoretical Chemistry, or a closely related discipline.
• Several years of post-PhD experience working in quantum computing, either within academia or industry.
• Strong experience in the development and analysis of quantum algorithms.
• Proven experience leading and developing a research team or group, including people management and mentoring responsibilities.
• Deep expertise in fault-tolerant quantum algorithms for quantum chemistry and materials applications.
• Strong knowledge of techniques including block encodings, qubitization, quantum signal processing and quantum singular value transformation.
• Hands‑on experience in quantum resource estimation and algorithmic cost analysis, particularly under realistic error‑correction assumptions.
• The ability to think end‑to‑end about the relationship between algorithm design, hardware capabilities and real-world application value