QuEra Computing, Inc. is seeking a Postdoctoral Fellow to help design and evaluate quantum machine learning algorithms that inform both near-term applications and long-term architectures for their neutral atom quantum computing platform.
Requirements
- Strong background in quantum learning theory and quantum information science.
- Experience developing and analyzing quantum algorithms.
- Demonstrated expertise in the implementation of quantum machine learning protocols on current hardware.
- Proficiency with numerical and software tools (e.g., Python, Julia, and TensorFlow, PyTorch, or equivalent machine learning library).
- Experience with classical machine learning, in particular, state-of-the-art generative models.
- Familiarity with neutral atom platforms, including Rydberg physics, optical lattices, or tweezer arrays.
- Familiarity with quantum error correction.
Responsibilities
- Develop and analyze quantum machine learning algorithms with the prospect of an advantage on suitable datasets.
- Design algorithms and quantum protocols suited to neutral atom platforms and collaborate with software teams on implementation.
- Collaborate with experimental teams to guide system design, interpret results, and validate models.
- Contribute to technical and research publications, white papers, and patent filings.
- Participate in internal knowledge-sharing sessions and external scientific outreach (e.g., conferences, workshops).
Other
- Ph.D. in Computer Science, Quantum Information, Math, Physics, or a closely related field.
- Track record of peer-reviewed publications in top-tier journals.
- Ability to work across theory and application space, spanning from formal mathematical foundations to practical applications and experimental demonstrations.
- Interest in translating fundamental research into commercial quantum technologies.
- This role is a fixed-term assignment.
