ZipRecruiter

Log In

1

Physics Informed Machine Learning Jobs in Boston, MA

Bayer

Principal Machine Learning Scientist

Cambridge, MA · On-site

$123K - $185K/yr

Principal Machine Learning Scientist The Principal Machine Learning Scientist will develop novel ... Experience with established, physics-based protein modelling methods like Molecular Dynamics and/or ...

Bayer

Principal Machine Learning Scientist

Cambridge, MA · On-site

$123K - $185K/yr

Principal Machine Learning Scientist The Principal Machine Learning Scientist will develop novel ... Experience with established, physics-based protein modelling methods like Molecular Dynamics and/or ...

next page

Showing results 1-20

All JobsPhysics Informed Machine Learning JobsPhysics Informed Machine Learning Jobs in Boston, MA

Physics Informed Machine Learning information

See Boston, MA salary details

$5

$21

$27

How much do physics informed machine learning jobs pay per hour?

As of Jun 21, 2026, the average hourly pay for physics informed machine learning in Boston, MA is $21.80, according to ZipRecruiter salary data. Most workers in this role earn between $13.56 and $27.69 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Physics Informed Machine Learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What is a Physics Informed Machine Learning job?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are popular job titles related to Physics Informed Machine Learning jobs in Boston, MA? For Physics Informed Machine Learning jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Physics Informed Machine Learning jobs in Boston, MA look for? The top searched job categories for Physics Informed Machine Learning jobs in Boston, MA are:
What cities near Boston, MA are hiring for Physics Informed Machine Learning jobs? Cities near Boston, MA with the most Physics Informed Machine Learning job openings:
Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in Boston, MA as of June 2026, with employment types broken down into 1% Locum Tenens, 79% Full Time, 15% Part Time, 1% Temporary, 2% Contract, and 2% Nights. Highlights an 72% Physical, 3% Hybrid, and 25% Remote job distribution, with an average salary of $45,336 per year, or $21.8 per hour.
Postdoctoral Fellow - Applied Machine Learning in Quantum Systems

Postdoctoral Fellow - Applied Machine Learning in Quantum Systems

QuEra Computing, Inc.

Boston, MA • On-site

$110K - $120K/yr

Full-time

Posted 24 days ago

Job description

Summary
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

Required Qualifications
  • 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.

Preferred Qualifications
  • 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.
#LI-NB1

Apply