Postdoctoral Fellow - Applied Machine Learning in Quantum Systems
Boston, MA, USA
- Pay
$110,000–120,000/year · BaseAnnual period assumed — pay source
Aware of advances in fault-tolerant quantum computing, in-the-loop control, and ML-driven control strategies. The approximate base salary range for this position is $110,000-$120,000. We consistently monitor external market data and update base salary ranges accordingly. We determine base compensation decisions on several factors, including as geographic placement, role-specific knowledge, skills, and/or experience. In addition to our base salary offerings, we also provide equity grants for all new hires.
Read the full posting- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingDevelop and deploy machine learning models for high-fidelity quantum operation inference and control prediction.
Design and prototype in-the-loop control mechanisms that adapt sequences based on measurement outcomes and system state.
Collaborate with physics, quantum error-correction, hardware, and control teams to validate new stack components using experimental data and system-level performance
From the employer’s posting
Key Responsibilities Develop and deploy machine learning models for high-fidelity quantum operation inference and control prediction. Design and prototype in-the-loop control mechanisms that adapt sequences based on measurement outcomes and system state.
Develop and deploy machine learning models for high-fidelity quantum operation inference and control prediction. Design and prototype in-the-loop control mechanisms that adapt sequences based on measurement outcomes and system state. Collaborate with physics, quantum error-correction, hardware, and control teams to validate new stack components using experimental data and system-level performance
Design and prototype in-the-loop control mechanisms that adapt sequences based on measurement outcomes and system state. Collaborate with physics, quantum error-correction, hardware, and control teams to validate new stack components using experimental data and system-level performance Required Qualifications
What you’ll bring
All qualificationsCore experience
- Experience working with quantum computing platforms (neutral atoms, trapped ions, superconducting qubits, or similar).
- Demonstrated experience working with Machine Learning for inference and hardware in loop.
- Proficiency with Git and modern collaborative development workflows.
Preferred experience
- Experience with quantum control stacks or real-time control systems.
- Familiarity with fault-tolerant protocols, logical qubit architectures, or quantum error correction frameworks.
- Experience with performance-sensitive, low-latency, or distributed systems.
Qualification wording
Experience working with quantum computing platforms (neutral atoms, trapped ions, superconducting qubits, or similar).
Demonstrated experience working with Machine Learning for inference and hardware in loop.
Proficiency with Git and modern collaborative development workflows.
Experience with quantum control stacks or real-time control systems.
Familiarity with fault-tolerant protocols, logical qubit architectures, or quantum error correction frameworks.
Experience with performance-sensitive, low-latency, or distributed systems.
Tools in this posting
- Python
- C++
Source — Tool mentions in context
- Demonstrated experience working with Machine Learning for inference and hardware in loop. - Strong programming skills in Python, C++, or similar languages. - Strong analytical and problem-solving skills, with the ability to take technical ownership.
Job description
This role focuses on developing computational methods for in-the-loop stabilization of neutral atom Logical Quantum Processing Units (LQPUs). The position sits at the interface of quantum hardware and control systems, supporting both near-term experimental performance and the long-term development of control architectures for stable, fault-tolerant computing.
The successful candidate will design and prototype state-of-the-art methods to enable reliable quantum operations and translate device measurements into actionable control feedback. Responsibilities include advancing capabilities such as measurement-informed feedback control and machine learning–driven inference.
Key Responsibilities
- Develop and deploy machine learning models for high-fidelity quantum operation inference and control prediction.
- Design and prototype in-the-loop control mechanisms that adapt sequences based on measurement outcomes and system state.
- Collaborate with physics, quantum error-correction, hardware, and control teams to validate new stack components using experimental data and system-level performance
- Ph.D. or equivalent experience in Physics, Computer Science, Electrical Engineering, or a related field, with a strong background in quantum computing or quantum physics.
- Experience working with quantum computing platforms (neutral atoms, trapped ions, superconducting qubits, or similar).
- Demonstrated experience working with Machine Learning for inference and hardware in loop.
- Strong programming skills in Python, C++, or similar languages.
- Strong analytical and problem-solving skills, with the ability to take technical ownership.
- Effective communication skills and the ability to collaborate across physics, engineering, and software teams.
- Proficiency with Git and modern collaborative development workflows.
- Track record of publications or significant technical contributions in relevant areas.
- Experience with quantum control stacks or real-time control systems.
- Familiarity with fault-tolerant protocols, logical qubit architectures, or quantum error correction frameworks.
- Experience with performance-sensitive, low-latency, or distributed systems.
- Aware of advances in fault-tolerant quantum computing, in-the-loop control, and ML-driven control strategies.
The approximate base salary range for this position is $110,000-$120,000.
We consistently monitor external market data and update base salary ranges accordingly. We determine base compensation decisions on several factors, including as geographic placement, role-specific knowledge, skills, and/or experience. In addition to our base salary offerings, we also provide equity grants for all new hires.
QuEra is committed to cultivating a diverse work environment and is proud to be an equal opportunity employer. We highly value diversity in our current and future employees and do not discriminate (including in our hiring and promotion practices) based on race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
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- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
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Source & posting history
Source notes
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- Pay
Aware of advances in fault-tolerant quantum computing, in-the-loop control, and ML-driven control strategies. The approximate base salary range for this position is $110,000-$120,000. We consistently monitor external market data and update base salary ranges accordingly. We determine base compensation decisions on several factors, including as geographic placement, role-specific knowledge, skills, and/or experience. In addition to our base salary offerings, we also provide equity grants for all new hires.
- Location & working pattern
Boston, MA, USA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Jun 2, 2026
- Recorded sightings
- 85
- Last seen by us
- Oct 8, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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