Summary

QuEra Computing is seeking a talented and innovative scientist with a strong background in quantum algorithms for materials and chemistry, quantum resource estimation, and quantum error correction. You will develop and adapt quantum algorithms for materials and chemistry problems, quantify their resource requirements on neutral-atom hardware, and identify co-design opportunities across algorithms, compilation, and error correction. You will work closely with external collaborators to translate their scientific goals into concrete quantum workloads on QuEra’s upcoming fault-tolerant neutral atom hardware. You will also collaborate with QuEra's software, QEC, and hardware teams to make sure that algorithmic approaches align with architectural capabilities and roadmaps. You will be expected to independently drive research efforts and turn your results into concrete guidance for project execution and hardware demonstrations.

Responsibilities

• Develop and adapt quantum algorithms for materials and chemistry problems, together with collaborators.
• Lead resource estimation to assess what these problems require on neutral-atom hardware, both near-term and fault-tolerant.
• Co-design algorithms, compilation, and error-correction strategies that make the most of QuEra's architecture.
• Support emulation and hardware demonstrations together with QuEra's internal teams.
• Represent QuEra in collaborative projects through technical reports, reviews, and publications.

Qualifications

• PhD in theoretical physics, chemistry, computer science, or a related field, or equivalent research experience
• Extensive research experience, with a publication record in quantum algorithms or quantum simulation
• Knowledge of quantum algorithms for materials and chemistry
• Experience in quantum resource estimation
• Knowledge of quantum error correction
• Strong scientific programming skills
• Ability to work independently and communicate clearly across disciplines and institutions

Preferred Qualifications

• Background in electronic-structure or classical many-body methods (e.g., DFT, DMRG, DMFT, QMC, embedding/downfolding)
• Knowledge of logical micro-architecture design
• Software engineering skills (maintainable, tested, version-controlled code)